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      "metadata": {
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        "_uuid": "dc8f67853b1710994ce99d1ee347191eca2c824e",
        "id": "kBommuwHDopt",
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      "source": [
        "!pip install tensorflow==2.14.1\n",
        "!pip install keras==2.14.0\n",
        "!pip install eli5\n",
        "!pip install shap\n",
        "!pip install scikeras"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting tensorflow==2.14.1\n",
            "  Downloading tensorflow-2.14.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (489.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m489.9/489.9 MB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: absl-py>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.4.0)\n",
            "Requirement already satisfied: astunparse>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.6.3)\n",
            "Requirement already satisfied: flatbuffers>=23.5.26 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (23.5.26)\n",
            "Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (0.5.4)\n",
            "Requirement already satisfied: google-pasta>=0.1.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (0.2.0)\n",
            "Requirement already satisfied: h5py>=2.9.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (3.9.0)\n",
            "Requirement already satisfied: libclang>=13.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (16.0.6)\n",
            "Requirement already satisfied: ml-dtypes==0.2.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (0.2.0)\n",
            "Requirement already satisfied: numpy<2.0.0,>=1.23.5 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.23.5)\n",
            "Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (3.3.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (23.2)\n",
            "Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (3.20.3)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (67.7.2)\n",
            "Requirement already satisfied: six>=1.12.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.16.0)\n",
            "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (2.4.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.6 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (4.5.0)\n",
            "Requirement already satisfied: wrapt<1.15,>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.14.1)\n",
            "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (0.34.0)\n",
            "Requirement already satisfied: grpcio<2.0,>=1.24.3 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (1.59.3)\n",
            "Requirement already satisfied: tensorboard<2.15,>=2.14 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (2.14.1)\n",
            "Requirement already satisfied: tensorflow-estimator<2.15,>=2.14.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (2.14.0)\n",
            "Requirement already satisfied: keras<2.15,>=2.14.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.14.1) (2.14.0)\n",
            "Requirement already satisfied: wheel<1.0,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from astunparse>=1.6.0->tensorflow==2.14.1) (0.42.0)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (2.17.3)\n",
            "Requirement already satisfied: google-auth-oauthlib<1.1,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (1.0.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (3.5.1)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (2.31.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (0.7.2)\n",
            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.15,>=2.14->tensorflow==2.14.1) (3.0.1)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (5.3.2)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (0.3.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (4.9)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<1.1,>=0.5->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (1.3.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (2023.11.17)\n",
            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard<2.15,>=2.14->tensorflow==2.14.1) (2.1.3)\n",
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            "Installing collected packages: tensorflow\n",
            "  Attempting uninstall: tensorflow\n",
            "    Found existing installation: tensorflow 2.14.0\n",
            "    Uninstalling tensorflow-2.14.0:\n",
            "      Successfully uninstalled tensorflow-2.14.0\n",
            "Successfully installed tensorflow-2.14.1\n",
            "Requirement already satisfied: keras==2.14.0 in /usr/local/lib/python3.10/dist-packages (2.14.0)\n",
            "Collecting eli5\n",
            "  Downloading eli5-0.13.0.tar.gz (216 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m216.2/216.2 kB\u001b[0m \u001b[31m4.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: eli5\n",
            "  Building wheel for eli5 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for eli5: filename=eli5-0.13.0-py2.py3-none-any.whl size=107717 sha256=0d913c72241a82fce35c9f46009f2cbe2fdffd234cdc485a7ce3e31b76456581\n",
            "  Stored in directory: /root/.cache/pip/wheels/b8/58/ef/2cf4c306898c2338d51540e0922c8e0d6028e07007085c0004\n",
            "Successfully built eli5\n",
            "Installing collected packages: eli5\n",
            "Successfully installed eli5-0.13.0\n",
            "Collecting shap\n",
            "  Downloading shap-0.44.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (533 kB)\n",
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            "Collecting slicer==0.0.7 (from shap)\n",
            "  Downloading slicer-0.0.7-py3-none-any.whl (14 kB)\n",
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            "Installing collected packages: slicer, shap\n",
            "Successfully installed shap-0.44.0 slicer-0.0.7\n",
            "Collecting scikeras\n",
            "  Downloading scikeras-0.12.0-py3-none-any.whl (27 kB)\n",
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            "Installing collected packages: scikeras\n",
            "Successfully installed scikeras-0.12.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fnzXIUbdRKdM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 44
        },
        "outputId": "ddf107f7-8feb-4fe6-8196-10aadaf83cdc"
      },
      "source": [
        "%matplotlib inline\n",
        "\n",
        "# libraries & dataset\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "sns.set(style=\"whitegrid\")\n",
        "sns.set_theme(style=\"white\")\n",
        "\n",
        "import keras\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense\n",
        "from scikeras.wrappers import KerasRegressor\n",
        "from keras import optimizers\n",
        "\n",
        "# Create a History callback to record training history\n",
        "from keras.callbacks import History\n",
        "\n",
        "history_callback = History()\n",
        "\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.model_selection import KFold\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "\n",
        "from sklearn import linear_model\n",
        "from sklearn.metrics import mean_squared_error, r2_score\n",
        "\n",
        "from scipy.stats import zscore\n",
        "from scipy.stats import f_oneway\n",
        "\n",
        "\n",
        "import eli5\n",
        "from eli5.sklearn import PermutationImportance\n",
        "\n",
        "# libraries & dataset\n",
        "from string import ascii_letters\n",
        "import shap\n",
        "\n",
        "# print the JS visualization code to the notebook\n",
        "shap.initjs()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
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t=e.stateNode;t.pendingContext?Aa(0,t.pendingContext,t.pendingContext!==t.context):t.context&&Aa(0,t.context,!1),ro(e,t.containerInfo)}function zu(e,t,n,r,a){return di(),hi(a),t.flags|=256,wu(e,t,n,r),t.child}var Lu,Ou,Au,Fu,Du={dehydrated:null,treeContext:null,retryLane:0};function Ru(e){return{baseLanes:e,cachePool:null,transitions:null}}function ju(e,t,n){var r,a=t.pendingProps,o=uo.current,u=!1,l=0!=(128&t.flags);if((r=l)||(r=(null===e||null!==e.memoizedState)&&0!=(2&o)),r?(u=!0,t.flags&=-129):null!==e&&null===e.memoizedState||(o|=1),Ca(uo,1&o),null===e)return si(t),null!==(e=t.memoizedState)&&null!==(e=e.dehydrated)?(0==(1&t.mode)?t.lanes=1:\"$!\"===e.data?t.lanes=8:t.lanes=1073741824,null):(l=a.children,e=a.fallback,u?(a=t.mode,u=t.child,l={mode:\"hidden\",children:l},0==(1&a)&&null!==u?(u.childLanes=0,u.pendingProps=l):u=Rs(l,a,0,null),e=Ds(e,a,n,null),u.return=t,e.return=t,u.sibling=e,t.child=u,t.child.memoizedState=Ru(n),t.memoizedState=Du,e):Uu(t,l));if(null!==(o=e.memoizedState)&&null!==(r=o.dehydrated))return function(e,t,n,r,a,o,u){if(n)return 256&t.flags?(t.flags&=-257,Iu(e,t,u,r=fu(Error(i(422))))):null!==t.memoizedState?(t.child=e.child,t.flags|=128,null):(o=r.fallback,a=t.mode,r=Rs({mode:\"visible\",children:r.children},a,0,null),(o=Ds(o,a,u,null)).flags|=2,r.return=t,o.return=t,r.sibling=o,t.child=r,0!=(1&t.mode)&&Ki(t,e.child,null,u),t.child.memoizedState=Ru(u),t.memoizedState=Du,o);if(0==(1&t.mode))return Iu(e,t,u,null);if(\"$!\"===a.data){if(r=a.nextSibling&&a.nextSibling.dataset)var l=r.dgst;return r=l,Iu(e,t,u,r=fu(o=Error(i(419)),r,void 0))}if(l=0!=(u&e.childLanes),_u||l){if(null!==(r=Pl)){switch(u&-u){case 4:a=2;break;case 16:a=8;break;case 64:case 128:case 256:case 512:case 1024:case 2048:case 4096:case 8192:case 16384:case 32768:case 65536:case 131072:case 262144:case 524288:case 1048576:case 2097152:case 4194304:case 8388608:case 16777216:case 33554432:case 67108864:a=32;break;case 536870912:a=268435456;break;default:a=0}0!==(a=0!=(a&(r.suspendedLanes|u))?0:a)&&a!==o.retryLane&&(o.retryLane=a,Ni(e,a),rs(r,e,a,-1))}return gs(),Iu(e,t,u,r=fu(Error(i(421))))}return\"$?\"===a.data?(t.flags|=128,t.child=e.child,t=Ms.bind(null,e),a._reactRetry=t,null):(e=o.treeContext,ri=sa(a.nextSibling),ni=t,ai=!0,ii=null,null!==e&&(Qa[Ya++]=Ka,Qa[Ya++]=Za,Qa[Ya++]=Ga,Ka=e.id,Za=e.overflow,Ga=t),(t=Uu(t,r.children)).flags|=4096,t)}(e,t,l,a,r,o,n);if(u){u=a.fallback,l=t.mode,r=(o=e.child).sibling;var s={mode:\"hidden\",children:a.children};return 0==(1&l)&&t.child!==o?((a=t.child).childLanes=0,a.pendingProps=s,t.deletions=null):(a=As(o,s)).subtreeFlags=14680064&o.subtreeFlags,null!==r?u=As(r,u):(u=Ds(u,l,n,null)).flags|=2,u.return=t,a.return=t,a.sibling=u,t.child=a,a=u,u=t.child,l=null===(l=e.child.memoizedState)?Ru(n):{baseLanes:l.baseLanes|n,cachePool:null,transitions:l.transitions},u.memoizedState=l,u.childLanes=e.childLanes&~n,t.memoizedState=Du,a}return e=(u=e.child).sibling,a=As(u,{mode:\"visible\",children:a.children}),0==(1&t.mode)&&(a.lanes=n),a.return=t,a.sibling=null,null!==e&&(null===(n=t.deletions)?(t.deletions=[e],t.flags|=16):n.push(e)),t.child=a,t.memoizedState=null,a}function Uu(e,t){return(t=Rs({mode:\"visible\",children:t},e.mode,0,null)).return=e,e.child=t}function Iu(e,t,n,r){return null!==r&&hi(r),Ki(t,e.child,null,n),(e=Uu(t,t.pendingProps.children)).flags|=2,t.memoizedState=null,e}function $u(e,t,n){e.lanes|=t;var r=e.alternate;null!==r&&(r.lanes|=t),ki(e.return,t,n)}function Bu(e,t,n,r,a){var i=e.memoizedState;null===i?e.memoizedState={isBackwards:t,rendering:null,renderingStartTime:0,last:r,tail:n,tailMode:a}:(i.isBackwards=t,i.rendering=null,i.renderingStartTime=0,i.last=r,i.tail=n,i.tailMode=a)}function Wu(e,t,n){var r=t.pendingProps,a=r.revealOrder,i=r.tail;if(wu(e,t,r.children,n),0!=(2&(r=uo.current)))r=1&r|2,t.flags|=128;else{if(null!==e&&0!=(128&e.flags))e:for(e=t.child;null!==e;){if(13===e.tag)null!==e.memoizedState&&$u(e,n,t);else if(19===e.tag)$u(e,n,t);else if(null!==e.child){e.child.return=e,e=e.child;continue}if(e===t)break e;for(;null===e.sibling;){if(null===e.return||e.return===t)break e;e=e.return}e.sibling.return=e.return,e=e.sibling}r&=1}if(Ca(uo,r),0==(1&t.mode))t.memoizedState=null;else switch(a){case\"forwards\":for(n=t.child,a=null;null!==n;)null!==(e=n.alternate)&&null===lo(e)&&(a=n),n=n.sibling;null===(n=a)?(a=t.child,t.child=null):(a=n.sibling,n.sibling=null),Bu(t,!1,a,n,i);break;case\"backwards\":for(n=null,a=t.child,t.child=null;null!==a;){if(null!==(e=a.alternate)&&null===lo(e)){t.child=a;break}e=a.sibling,a.sibling=n,n=a,a=e}Bu(t,!0,n,null,i);break;case\"together\":Bu(t,!1,null,null,void 0);break;default:t.memoizedState=null}return t.child}function Vu(e,t){0==(1&t.mode)&&null!==e&&(e.alternate=null,t.alternate=null,t.flags|=2)}function Hu(e,t,n){if(null!==e&&(t.dependencies=e.dependencies),Rl|=t.lanes,0==(n&t.childLanes))return null;if(null!==e&&t.child!==e.child)throw Error(i(153));if(null!==t.child){for(n=As(e=t.child,e.pendingProps),t.child=n,n.return=t;null!==e.sibling;)e=e.sibling,(n=n.sibling=As(e,e.pendingProps)).return=t;n.sibling=null}return t.child}function qu(e,t){if(!ai)switch(e.tailMode){case\"hidden\":t=e.tail;for(var n=null;null!==t;)null!==t.alternate&&(n=t),t=t.sibling;null===n?e.tail=null:n.sibling=null;break;case\"collapsed\":n=e.tail;for(var r=null;null!==n;)null!==n.alternate&&(r=n),n=n.sibling;null===r?t||null===e.tail?e.tail=null:e.tail.sibling=null:r.sibling=null}}function Qu(e){var t=null!==e.alternate&&e.alternate.child===e.child,n=0,r=0;if(t)for(var a=e.child;null!==a;)n|=a.lanes|a.childLanes,r|=14680064&a.subtreeFlags,r|=14680064&a.flags,a.return=e,a=a.sibling;else for(a=e.child;null!==a;)n|=a.lanes|a.childLanes,r|=a.subtreeFlags,r|=a.flags,a.return=e,a=a.sibling;return e.subtreeFlags|=r,e.childLanes=n,t}function Yu(e,t,n){var r=t.pendingProps;switch(ti(t),t.tag){case 2:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return Qu(t),null;case 1:case 17:return La(t.type)&&Oa(),Qu(t),null;case 3:return r=t.stateNode,ao(),Ea(Na),Ea(Ma),co(),r.pendingContext&&(r.context=r.pendingContext,r.pendingContext=null),null!==e&&null!==e.child||(fi(t)?t.flags|=4:null===e||e.memoizedState.isDehydrated&&0==(256&t.flags)||(t.flags|=1024,null!==ii&&(us(ii),ii=null))),Ou(e,t),Qu(t),null;case 5:oo(t);var a=no(to.current);if(n=t.type,null!==e&&null!=t.stateNode)Au(e,t,n,r,a),e.ref!==t.ref&&(t.flags|=512,t.flags|=2097152);else{if(!r){if(null===t.stateNode)throw Error(i(166));return Qu(t),null}if(e=no(Ji.current),fi(t)){r=t.stateNode,n=t.type;var 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r.is?e=l.createElement(n,{is:r.is}):(e=l.createElement(n),\"select\"===n&&(l=e,r.multiple?l.multiple=!0:r.size&&(l.size=r.size))):e=l.createElementNS(e,n),e[pa]=t,e[da]=r,Lu(e,t,!1,!1),t.stateNode=e;e:{switch(l=be(n,r),n){case\"dialog\":Ur(\"cancel\",e),Ur(\"close\",e),a=r;break;case\"iframe\":case\"object\":case\"embed\":Ur(\"load\",e),a=r;break;case\"video\":case\"audio\":for(a=0;a<Fr.length;a++)Ur(Fr[a],e);a=r;break;case\"source\":Ur(\"error\",e),a=r;break;case\"img\":case\"image\":case\"link\":Ur(\"error\",e),Ur(\"load\",e),a=r;break;case\"details\":Ur(\"toggle\",e),a=r;break;case\"input\":K(e,r),a=G(e,r),Ur(\"invalid\",e);break;case\"option\":default:a=r;break;case\"select\":e._wrapperState={wasMultiple:!!r.multiple},a=R({},r,{value:void 0}),Ur(\"invalid\",e);break;case\"textarea\":ae(e,r),a=re(e,r),Ur(\"invalid\",e)}for(o in me(n,a),s=a)if(s.hasOwnProperty(o)){var c=s[o];\"style\"===o?ge(e,c):\"dangerouslySetInnerHTML\"===o?null!=(c=c?c.__html:void 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Error(i(166));if(n=no(to.current),no(Ji.current),fi(t)){if(r=t.stateNode,n=t.memoizedProps,r[pa]=t,(o=r.nodeValue!==n)&&null!==(e=ni))switch(e.tag){case 3:Xr(r.nodeValue,n,0!=(1&e.mode));break;case 5:!0!==e.memoizedProps.suppressHydrationWarning&&Xr(r.nodeValue,n,0!=(1&e.mode))}o&&(t.flags|=4)}else(r=(9===n.nodeType?n:n.ownerDocument).createTextNode(r))[pa]=t,t.stateNode=r}return Qu(t),null;case 13:if(Ea(uo),r=t.memoizedState,null===e||null!==e.memoizedState&&null!==e.memoizedState.dehydrated){if(ai&&null!==ri&&0!=(1&t.mode)&&0==(128&t.flags))pi(),di(),t.flags|=98560,o=!1;else if(o=fi(t),null!==r&&null!==r.dehydrated){if(null===e){if(!o)throw Error(i(318));if(!(o=null!==(o=t.memoizedState)?o.dehydrated:null))throw Error(i(317));o[pa]=t}else di(),0==(128&t.flags)&&(t.memoizedState=null),t.flags|=4;Qu(t),o=!1}else null!==ii&&(us(ii),ii=null),o=!0;if(!o)return 65536&t.flags?t:null}return 0!=(128&t.flags)?(t.lanes=n,t):((r=null!==r)!=(null!==e&&null!==e.memoizedState)&&r&&(t.child.flags|=8192,0!=(1&t.mode)&&(null===e||0!=(1&uo.current)?0===Fl&&(Fl=3):gs())),null!==t.updateQueue&&(t.flags|=4),Qu(t),null);case 4:return ao(),Ou(e,t),null===e&&Br(t.stateNode.containerInfo),Qu(t),null;case 10:return xi(t.type._context),Qu(t),null;case 19:if(Ea(uo),null===(o=t.memoizedState))return Qu(t),null;if(r=0!=(128&t.flags),null===(l=o.rendering))if(r)qu(o,!1);else{if(0!==Fl||null!==e&&0!=(128&e.flags))for(e=t.child;null!==e;){if(null!==(l=lo(e))){for(t.flags|=128,qu(o,!1),null!==(r=l.updateQueue)&&(t.updateQueue=r,t.flags|=4),t.subtreeFlags=0,r=n,n=t.child;null!==n;)e=r,(o=n).flags&=14680066,null===(l=o.alternate)?(o.childLanes=0,o.lanes=e,o.child=null,o.subtreeFlags=0,o.memoizedProps=null,o.memoizedState=null,o.updateQueue=null,o.dependencies=null,o.stateNode=null):(o.childLanes=l.childLanes,o.lanes=l.lanes,o.child=l.child,o.subtreeFlags=0,o.deletions=null,o.memoizedProps=l.memoizedProps,o.memoizedState=l.memoizedState,o.updateQueue=l.updateQueue,o.type=l.type,e=l.dependencies,o.dependencies=null===e?null:{lanes:e.lanes,firstContext:e.firstContext}),n=n.sibling;return Ca(uo,1&uo.current|2),t.child}e=e.sibling}null!==o.tail&&Ze()>Wl&&(t.flags|=128,r=!0,qu(o,!1),t.lanes=4194304)}else{if(!r)if(null!==(e=lo(l))){if(t.flags|=128,r=!0,null!==(n=e.updateQueue)&&(t.updateQueue=n,t.flags|=4),qu(o,!0),null===o.tail&&\"hidden\"===o.tailMode&&!l.alternate&&!ai)return Qu(t),null}else 2*Ze()-o.renderingStartTime>Wl&&1073741824!==n&&(t.flags|=128,r=!0,qu(o,!1),t.lanes=4194304);o.isBackwards?(l.sibling=t.child,t.child=l):(null!==(n=o.last)?n.sibling=l:t.child=l,o.last=l)}return null!==o.tail?(t=o.tail,o.rendering=t,o.tail=t.sibling,o.renderingStartTime=Ze(),t.sibling=null,n=uo.current,Ca(uo,r?1&n|2:1&n),t):(Qu(t),null);case 22:case 23:return ps(),r=null!==t.memoizedState,null!==e&&null!==e.memoizedState!==r&&(t.flags|=8192),r&&0!=(1&t.mode)?0!=(1073741824&Ol)&&(Qu(t),6&t.subtreeFlags&&(t.flags|=8192)):Qu(t),null;case 24:case 25:return null}throw Error(i(156,t.tag))}function Gu(e,t){switch(ti(t),t.tag){case 1:return La(t.type)&&Oa(),65536&(e=t.flags)?(t.flags=-65537&e|128,t):null;case 3:return ao(),Ea(Na),Ea(Ma),co(),0!=(65536&(e=t.flags))&&0==(128&e)?(t.flags=-65537&e|128,t):null;case 5:return oo(t),null;case 13:if(Ea(uo),null!==(e=t.memoizedState)&&null!==e.dehydrated){if(null===t.alternate)throw Error(i(340));di()}return 65536&(e=t.flags)?(t.flags=-65537&e|128,t):null;case 19:return Ea(uo),null;case 4:return ao(),null;case 10:return xi(t.type._context),null;case 22:case 23:return ps(),null;default:return null}}Lu=function(e,t){for(var n=t.child;null!==n;){if(5===n.tag||6===n.tag)e.appendChild(n.stateNode);else if(4!==n.tag&&null!==n.child){n.child.return=n,n=n.child;continue}if(n===t)break;for(;null===n.sibling;){if(null===n.return||n.return===t)return;n=n.return}n.sibling.return=n.return,n=n.sibling}},Ou=function(){},Au=function(e,t,n,r){var a=e.memoizedProps;if(a!==r){e=t.stateNode,no(Ji.current);var 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t,n={},r={},a={},i=Ga(this.props.explanations);try{for(i.s();!(t=i.n()).done;){var o=t.value;for(var u in o.features)void 0===n[u]&&(n[u]=0,r[u]=0,a[u]=0),o.features[u].effect>0?n[u]+=o.features[u].effect:r[u]-=o.features[u].effect,null!==o.features[u].value&&void 0!==o.features[u].value&&(a[u]+=1)}}catch(e){i.e(e)}finally{i.f()}this.usedFeatures=(0,Re.sortBy)((0,Re.keys)(n),(function(e){return-(n[e]+r[e])})),console.log(\"found \",this.usedFeatures.length,\" used features\"),this.posOrderedFeatures=(0,Re.sortBy)(this.usedFeatures,(function(e){return n[e]})),this.negOrderedFeatures=(0,Re.sortBy)(this.usedFeatures,(function(e){return-r[e]})),this.singleValueFeatures=(0,Re.filter)(this.usedFeatures,(function(e){return a[e]>0}));var l=[\"sample order by similarity\",\"sample order by output value\",\"original sample ordering\"].concat(this.singleValueFeatures.map((function(t){return e.props.featureNames[t]})));null!=this.props.ordering_keys&&l.unshift(\"sample order by key\");var s=this.xlabel.selectAll(\"option\").data(l);s.enter().append(\"option\").merge(s).attr(\"value\",(function(e){return e})).text((function(e){return e})),s.exit().remove();var c=this.props.outNames[0]?this.props.outNames[0]:\"model output value\";(l=(0,Re.map)(this.usedFeatures,(function(t){return[e.props.featureNames[t],e.props.featureNames[t]+\" effects\"]}))).unshift([\"model output value\",c]);var f=this.ylabel.selectAll(\"option\").data(l);f.enter().append(\"option\").merge(f).attr(\"value\",(function(e){return e[0]})).text((function(e){return e[1]})),f.exit().remove(),this.ylabel.style(\"top\",(this.height-10-this.topOffset)/2+this.topOffset+\"px\").style(\"left\",10-this.ylabel.node().offsetWidth/2+\"px\"),this.internalDraw()}}},{key:\"internalDraw\",value:function(){var e,t,n=this,r=Ga(this.props.explanations);try{for(r.s();!(e=r.n()).done;){var a,i=e.value,o=Ga(this.usedFeatures);try{for(o.s();!(a=o.n()).done;){var 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              "</script>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Read CSV file into a DataFrame\n",
        "raw_dataset = pd.read_csv('database.csv', sep=',')\n",
        "df = raw_dataset.copy()\n",
        "\n",
        "# Filter data for Descriptor T30 and STI\n",
        "filtered_df = df[df['Descriptor'].isin(['T30', 'STI'])]\n",
        "\n",
        "# Map Descriptor values to units\n",
        "unit_mapping = {'T30': 'seconds [s]', 'STI': 'dimensionless'}\n",
        "filtered_df['Descriptor'] = filtered_df['Descriptor'].map(unit_mapping)\n",
        "\n",
        "# Define a scientific color palette\n",
        "scientific_palette = ['#1f77b4', '#ff7f0e']\n",
        "\n",
        "# Set plotting style to whitegrid\n",
        "sns.set_style(\"whitegrid\")\n",
        "\n",
        "# Create a boxplot with data distribution\n",
        "plt.figure(figsize=(10, 6))\n",
        "ax = sns.boxplot(x=\"Classroom_id\",\n",
        "                 y=\"Value\",\n",
        "                 hue=\"Descriptor\",\n",
        "                 data=filtered_df,\n",
        "                 palette=scientific_palette, width=0.5)\n",
        "\n",
        "# Add strip plot for data distribution\n",
        "sns.stripplot(x=\"Classroom_id\",\n",
        "              y=\"Value\",\n",
        "              hue=\"Descriptor\",\n",
        "              data=filtered_df,\n",
        "              color='#ff7f0e',\n",
        "              dodge=True,\n",
        "              alpha=0.5)\n",
        "\n",
        "# Set x-axis label\n",
        "ax.set_xlabel(\"Classroom ID\")\n",
        "\n",
        "# Set y-axis label with unit information\n",
        "ax.set_ylabel(f\"T30 / STI ({unit_mapping['T30']} / {unit_mapping['STI']})\")\n",
        "\n",
        "# Add legend with descriptor names and set STI box to be orange\n",
        "legend = ax.legend(title='Descriptor',\n",
        "                   loc='upper right',\n",
        "                   labels=['T30', 'STI'])\n",
        "\n",
        "legend.legendHandles[1].set_facecolor('#ff7f0e')  # Set color for STI box\n",
        "\n",
        "# Remove grid lines\n",
        "ax.yaxis.grid(False)\n",
        "\n",
        "# Show the plot\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "n7h9xu7GwkDy",
        "outputId": "5875fdeb-f35d-4df5-9eb6-00a16e4e1316"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting a gradient palette using color= is deprecated and will be removed in version 0.13. Set `palette='dark:#ff7f0e'` for same effect.\n",
            "The legendHandles attribute was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use legend_handles instead.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 848
        },
        "id": "RykwA85wb7Pt",
        "outputId": "084f6a6a-10b6-431f-85da-e73948d33b7e"
      },
      "source": [
        "# Generate dataset\n",
        "raw_dataset = pd.read_csv('/content/data_to_correlation.csv', sep=',')\n",
        "d = raw_dataset.copy()\n",
        "df.tail()\n",
        "\n",
        "# Compute the correlation matrix\n",
        "corr = d.corr()\n",
        "\n",
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=1.0, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 4
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1100x900 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.stats import linregress\n",
        "\n",
        "\n",
        "def auto_sensitivy_analisys(raw_dataset_file, x_label, y_label):\n",
        "\n",
        "  # Load entire dataset for training\n",
        "  raw_dataset = pd.read_csv(raw_dataset_file, sep=',')\n",
        "  df = raw_dataset.copy()\n",
        "  df.tail()\n",
        "\n",
        "  # Set up variables to the tranings variables\n",
        "  df = df.sort_index()\n",
        "\n",
        "  df = df[y_label + x_label]\n",
        "  df = df.dropna()\n",
        "  df.tail()\n",
        "\n",
        "  # Split the data into test and training sets.\n",
        "  np.random.seed(100)\n",
        "  X_train, X_test, y_train, y_test = train_test_split(df[x_label],\n",
        "                                                      df[y_label],\n",
        "                                                      test_size=0.01)\n",
        "  # Print the dimensions\n",
        "  print('Training set dimensions X, y: ' + str(X_train.shape) + ' ' +str(y_train.shape))\n",
        "  print('Test set dimensions X, y: ' + str(X_test.shape) + ' '+ str(y_test.shape))\n",
        "\n",
        "\n",
        "  # Define regression model in Keras\n",
        "  def DL_regression_model():\n",
        "      model = Sequential()\n",
        "      model.add(Dense(8, input_dim=4, activation='relu'))\n",
        "      model.add(Dense(4, activation='relu'))\n",
        "      model.add(Dense(2, activation='relu'))\n",
        "      model.add(Dense(1, activation='linear'))\n",
        "\n",
        "      # Compile model\n",
        "      adam = optimizers.Adam(0.01)\n",
        "      model.compile(loss='mean_squared_error',\n",
        "                    optimizer=adam,\n",
        "                    metrics=['mse'])\n",
        "\n",
        "      return model\n",
        "\n",
        "  # O parâmetro patience é o quantidade de epochs para checar as melhoras\n",
        "  early_stop = keras.callbacks.EarlyStopping(monitor='val_loss',\n",
        "                                             patience=5)\n",
        "\n",
        "  estimator = KerasRegressor(build_fn=DL_regression_model,\n",
        "                            validation_split = 0.1,\n",
        "                            batch_size=2,\n",
        "                            loss='mse',\n",
        "                            epochs=20,\n",
        "                            verbose=0,\n",
        "                            callbacks=[early_stop,\n",
        "                                       history_callback]\n",
        "                            )\n",
        "\n",
        "  history = estimator.fit(X_train, y_train)\n",
        "\n",
        "  print(DL_regression_model)\n",
        "\n",
        "  isPlot = False\n",
        "\n",
        "  if isPlot == True:\n",
        "   # Plot training & validation loss values\n",
        "\n",
        "   plt.plot(history_callback.history['loss'])\n",
        "   plt.plot(history_callback.history['val_loss'])\n",
        "   plt.title('Model loss')\n",
        "   plt.xlabel('Epoch')\n",
        "   plt.ylabel('Loss')\n",
        "   plt.legend(['Train', 'Validation'], loc='upper right')\n",
        "   plt.show()\n",
        "\n",
        "\n",
        "  isCross = False\n",
        "\n",
        "  if isCross == True:\n",
        "    # Cross validation\n",
        "\n",
        "    kfold = KFold(n_splits=4)\n",
        "    result = cross_val_score(estimator,\n",
        "                            X_train.values,\n",
        "                            y_train.values,\n",
        "                            cv=kfold,\n",
        "                            n_jobs=1)\n",
        "\n",
        "    print(\"Results: %.2f (%.2f) MSE\" % (result.mean(), result.std()))\n",
        "\n",
        "    # Assuming 'result' is the array of cross-validation results\n",
        "    cv_results = pd.DataFrame({'Fold': range(1, len(result) + 1), 'MSE': result})\n",
        "\n",
        "    # Display the table\n",
        "    print(cv_results)\n",
        "\n",
        "  # Fitting resuts\n",
        "\n",
        "  fitted = estimator.predict(X_train)\n",
        "  residuals = y_train[y_label[0]].values - fitted\n",
        "\n",
        "  # Two plots\n",
        "  fig, (ax1, ax2) = plt.subplots(ncols=2,figsize=(12,6))\n",
        "\n",
        "  # 1. Histogram of residuals\n",
        "  sns.distplot(residuals, ax=ax1)\n",
        "  ax1.set_title('Histogram of residuals')\n",
        "\n",
        "  # Fitted vs residuals\n",
        "  x1 = pd.Series(fitted.reshape(15), name='Fitted total')\n",
        "  x2 = pd.Series(y_train[y_label[0]], name=\"total values\")\n",
        "\n",
        "  #sns.kdeplot(x1, n_levels=5,ax = ax2)\n",
        "  sns.regplot(x=x1, y=x2, scatter=False, ax = ax2)\n",
        "  ax2.set_title('Fitted vs actual values')\n",
        "  ax2.set_xlim([0,1])\n",
        "  ax2.set_ylim([0,1])\n",
        "  ax2.set_aspect('equal')\n",
        "\n",
        "  # Calculate linear DL model regression parameters\n",
        "  DL_slope, intercept, r_value, p_value, std_err = linregress(y_train[y_label[0]].values,\n",
        "                                                              fitted.reshape(15))\n",
        "\n",
        "  # Print the slope coefficient\n",
        "  print(f\"Slope Coefficient: {DL_slope}\")\n",
        "\n",
        "  plt.show()\n",
        "\n",
        "  # Permutation model\n",
        "  perm = PermutationImportance(estimator,\n",
        "                               random_state=8).fit(X_train,y_train)\n",
        "\n",
        "  perm_importances = eli5.explain_weights_df(perm, feature_names=X_train.columns.tolist())\n",
        "\n",
        "  # SHAP expects model functions to take a 2D numpy array as input,\n",
        "  # so we define a wrapper function around the original Keras predict function.\n",
        "  def f_wrapper(X):\n",
        "      return estimator.predict(X).flatten()\n",
        "\n",
        "  X_train_summary = shap.kmeans(X_train, 10)\n",
        "  X_train_summary = X_train_summary.data.astype(int)\n",
        "\n",
        "  # Compute Shap values\n",
        "  explainer = shap.KernelExplainer(f_wrapper, X_train_summary)\n",
        "\n",
        "  # Create subplots\n",
        "  plt.figure(1)\n",
        "  # Make plot with combined shap values\n",
        "  X_train_sample = X_train.sample(10)\n",
        "  shap_values  = explainer.shap_values(X_train_sample)\n",
        "  shap.summary_plot(shap_values, X_train_sample)\n",
        "  plt.show()\n",
        "\n",
        "  print(shap_values)\n",
        "\n",
        "  column_means = shap_values.max(axis=0)\n",
        "\n",
        "  print(\"Shape values\", column_means.sort)\n",
        "  print(\"Shape values\", np.sort(column_means))\n",
        "\n",
        "  if isPlot == True:\n",
        "   # Dependence plots\n",
        "   shap.dependence_plot(0, shap_values, X_train_sample)\n",
        "   shap.dependence_plot(1, shap_values, X_train_sample)\n",
        "   shap.dependence_plot(2, shap_values, X_train_sample)\n",
        "   shap.dependence_plot(3, shap_values, X_train_sample)\n",
        "\n",
        "  shape_result = np.mean(shap_values, axis=0)\n",
        "  print(\"Shap values final\", shape_result)\n",
        "\n",
        "  # Create linear regression object\n",
        "  regr = linear_model.LinearRegression()\n",
        "\n",
        "  # Train the model using the training sets\n",
        "  regr.fit(X_train, y_train)\n",
        "\n",
        "  # Make predictions using the testing set\n",
        "  y_pred = regr.predict(X_train)\n",
        "\n",
        "  # The coefficients\n",
        "  print('Coefficients: \\n', regr.coef_)\n",
        "  # The mean squared error\n",
        "  print('Mean squared error: %.2f'\n",
        "        % mean_squared_error(y_train, y_pred))\n",
        "  # The coefficient of determination: 1 is perfect prediction\n",
        "  print('Coefficient of determination: %.2f'\n",
        "        % r2_score(y_train, y_pred))\n",
        "\n",
        "  return y_label[0], perm_importances['weight'].values, shape_result, regr.coef_[0], DL_slope\n"
      ],
      "metadata": {
        "id": "AI8piosbwGED"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "raw_dataset.columns.values"
      ],
      "metadata": {
        "id": "FKyTGmouw2kw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "51b45572-94d1-4e60-9393-f310e60c1a71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Class 1 - T30', 'Class 2 - T30', 'Class 3 - T30', 'Class 4 - T30',\n",
              "       'Class 5 - T30', 'Class 1 - STI', 'Class 2 - STI', 'Class 3 - STI',\n",
              "       'Class 4 - STI', 'Class 5 - STI'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_label = ['A',\t'B',\t'C',\t'D']\n",
        "raw_dataset_file = '/content/training_dataset.csv'\n",
        "result = []\n",
        "\n",
        "for class_id in raw_dataset.columns.values:\n",
        "    print(f\"Evaluating classroom: {class_id}\")\n",
        "\n",
        "    while True:\n",
        "        partial_resul = auto_sensitivy_analisys(raw_dataset_file, x_label, [class_id])\n",
        "        if partial_resul[2].mean() != 0 or partial_resul[4] > 0.9:\n",
        "            result.append(partial_resul[:-1])\n",
        "            break  # Exit the loop if the condition is met"
      ],
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        },
        "id": "UZnqhxDMZb_U",
        "outputId": "f7e5931b-3f11-430d-a572-bb2a41801456"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Evaluating classroom: Class 1 - T30\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbba8c0d1b0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.6622036894041897\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dad994c6c965479e955b9b1df57a5276"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.019722   -0.10978085  0.04118198 -0.00604939]\n",
            " [ 0.00861451 -0.06683198 -0.00095176  0.04854783]\n",
            " [-0.00965422 -0.05291691 -0.01572005 -0.04276023]\n",
            " [-0.0296959   0.03667073  0.02236027  0.04478509]\n",
            " [-0.00824867 -0.04998423  0.04384693 -0.01751552]\n",
            " [-0.0419967   0.02572093 -0.01445953 -0.05266192]\n",
            " [ 0.02090354 -0.09947613 -0.01579792 -0.02510101]\n",
            " [ 0.03974038  0.05230211 -0.00923568  0.04328648]\n",
            " [ 0.04155864  0.05689445  0.02514711  0.02456229]\n",
            " [-0.02810164  0.03034129 -0.00861001  0.05718156]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbba1fc0330>\n",
            "Shape values [0.04155864 0.04384693 0.05689445 0.05718156]\n",
            "Shap values final [ 0.00128419 -0.01770606  0.00677613  0.00742752]\n",
            "Coefficients: \n",
            " [[-0.00042614 -0.08785511 -0.00839489 -0.03183239]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.89\n",
            "Evaluating classroom: Class 2 - T30\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbba80e7370>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.014423736143132365\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3617a5b157ff4450a25f9df5eb4702bf"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.00384892 -0.00606676  0.03539174  0.03526635]\n",
            " [-0.00217039 -0.00519811 -0.0229193  -0.01000388]\n",
            " [-0.01950245 -0.01141195 -0.02509079  0.01571351]\n",
            " [ 0.02453845  0.00492649  0.05653928 -0.00439088]\n",
            " [-0.00206758  0.00541301  0.0599957   0.02070737]\n",
            " [-0.01956753  0.00798013 -0.01796611  0.02083954]\n",
            " [ 0.0210168  -0.01250738 -0.015092    0.033526  ]\n",
            " [ 0.00157728  0.00324347 -0.01038767 -0.03472476]\n",
            " [-0.02340814 -0.00141184  0.02282093 -0.03829263]\n",
            " [-0.00071396  0.00320062 -0.02690715 -0.01587119]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbba1399830>\n",
            "Shape values [0.00798013 0.02453845 0.03526635 0.0599957 ]\n",
            "Shap values final [-0.00164486 -0.00118323  0.00563846  0.00227694]\n",
            "Coefficients: \n",
            " [[ 0.01014205 -0.1618608   0.0865483  -0.0562642 ]]\n",
            "Mean squared error: 0.01\n",
            "Coefficient of determination: 0.76\n",
            "Evaluating classroom: Class 3 - T30\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbba158f6d0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.9447388169451713\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "86e035eb18394ee78c7b1f445bd9ad23"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.01166481 -0.23013576  0.10838874 -0.09757703]\n",
            " [ 0.00761925 -0.24704509 -0.07566655  0.04066474]\n",
            " [ 0.00540331 -0.20636277 -0.06065285 -0.05368153]\n",
            " [ 0.01844169  0.12165451  0.22303528  0.12199277]\n",
            " [ 0.00878005 -0.24177059  0.11485586 -0.07769762]\n",
            " [ 0.03171065  0.07372349 -0.07580235 -0.08402329]\n",
            " [-0.00771062 -0.17110441 -0.05978905 -0.05467145]\n",
            " [-0.00736609  0.09126264 -0.10070589  0.09422029]\n",
            " [-0.02207279  0.10624949  0.20611924  0.12223438]\n",
            " [ 0.00431242  0.08954026 -0.11262582  0.06682206]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb99540150>\n",
            "Shape values [0.03171065 0.12165451 0.12223438 0.22303528]\n",
            "Shap values final [ 0.00274531 -0.06139882  0.01671566  0.00782833]\n",
            "Coefficients: \n",
            " [[ 0.00610795 -0.17579545  0.12079545 -0.07764205]]\n",
            "Mean squared error: 0.01\n",
            "Coefficient of determination: 0.83\n",
            "Evaluating classroom: Class 4 - T30\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb99792200>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.0019623976874297124\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b3262114f02a465ba1c33b2ff8049030"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.00277362 -0.00397954 -0.00494428 -0.00277362]\n",
            " [ 0.          0.          0.          0.        ]\n",
            " [ 0.00012059 -0.00012059  0.00012059 -0.00012059]\n",
            " [ 0.00012059  0.00012059 -0.00036178  0.00012059]\n",
            " [ 0.00253243 -0.00060296 -0.00132651 -0.00060296]\n",
            " [ 0.          0.          0.          0.        ]\n",
            " [-0.00036178 -0.00060296  0.00132651 -0.00036178]\n",
            " [ 0.          0.          0.          0.        ]\n",
            " [-0.00012059  0.00036178 -0.00060296  0.00036178]\n",
            " [ 0.          0.          0.          0.        ]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb9935de30>\n",
            "Shape values [0.00036178 0.00036178 0.00132651 0.00253243]\n",
            "Shap values final [-4.82368469e-05 -4.82368469e-04 -5.78842163e-04 -3.37657928e-04]\n",
            "Coefficients: \n",
            " [[ 0.015625  -0.2946875  0.0325    -0.1646875]]\n",
            "Mean squared error: 0.03\n",
            "Coefficient of determination: 0.78\n",
            "Evaluating classroom: Class 5 - T30\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb993525f0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.9807233824690651\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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eOj0v3zeqbzhhuAppaWkQRRFyudzXpRAREQEArFYrBEFAcnKyr0shqhfWrl2Lp59++rqvPfLII5gwYUKl9h07duDQoUOYOXNmhXaj0YiPP/4YvXr1Qu/evb1SbyDZv38/UlNTMXnyZGi1Wl+XQ0Rg+K+SKIrwxXIIoijCarVCLpdDEIQ6P39dakjXCvB6A11Dut6GdK2Af10vl+khqplZs2ahWbNmFdratWuH2NhYHDp0qMICujt27MAXX3xx3fC/ZMkSPPHEEwz/LkhLS8OSJUswZswYhn8iP8HwX4XyHv8uXbrU6XlLS0tx/PhxtGnTBkFBQXV67rrWkK4V4PUGuoZ0vQ3pWgH/ut7Dhw/79PxE9dWAAQOq/JtOqVTWcTVERL7BOf9ERERE1CD9fc7/vHnz8MUXXwAAEhISnP9kZWWhb9++AIAlS5Y42xcvXuw81pkzZzBr1iz06tULXbp0wdixY7Ft27ZK50xPT8cDDzyAxMREDBgwAO+99x4cDscNa126dCkSEhJw8eLFSq8tWLAAnTt3RnFxMQAgMzMTM2fOREpKCrp06YIBAwZgzpw50Ov11Z7jjz/+wKxZs3DzzTejc+fOGDhwIF555RWYTKZK2545cwZPPvkk+vTpg8TERAwdOhQLFy4EACxevBjz588HAAwePLjCfaxunYW/39OLFy/i+eefx9ChQ5GYmIjevXtj1qxZNZpjv3nzZiQkJOD333+v9Nrq1auRkJCAU6dOAQBOnDiBefPmYfDgwejSpQtSUlLw9NNPo7Cw8Ibn+fs1lBs0aBDmzZtXoU2n0+Hll1/GwIED0blzZwwZMgQffvhhpe+HDRs2YOzYsUhOTka3bt1wxx13YPny5e5cPhEA9vwTERERUYAzGAwoKCio0BYREVFpu/Hjx+PKlStITU11htfybZ9//nk8//zzGDJkCIYMGQKgLOgBZYF+4sSJiI6OxiOPPIKgoCBs2rQJM2bMwOLFi53b5+bm4oEHHoDdbsejjz4KtVqNNWvWuDT6YPjw4XjjjTewadMmPPzwwxVe27RpE1JSUhAaGgqLxYKHHnoIFosF9913Hxo1aoScnBxs374dOp0OISEhVZ5j8+bNMJlMmDhxIsLCwnDo0CF8/vnnuHz5Mt555x3ndidOnMC9994LmUyG8ePHIzY2FufPn8fPP/+MOXPmYMiQIcjMzMQPP/yAp59+GuHh4c77+Pf3oTqHDx9GWloaRowYgSZNmuDixYtYtWoVHnjgAWzYsAFqtdrlY918883O96VXr14VXtu4cSPatm2Ldu3aAQB27dqFCxcuYOzYsYiKikJ6ejrWrFmD06dPY82aNR6ZAmY0GnHfffchJycHEyZMQNOmTZGWloa33noLubm5+Pe//w0ASE1Nxdy5c9G3b1/84x//AABkZGRg//79mDx5cq3roIaF4Z+IiIiIAtqUKVMqtZ08ebJSW3JyMuLi4pCamopRo0ZVeG3o0KF4/vnnkZCQUOm1l19+GU2bNsU333wDhUIBAJg0aRImTpyIN9980xn+P/roIxQUFOCrr75CYmIiAGDMmDG47bbbbngNMTExSEpKwsaNGyuE/0OHDuHChQt44oknAJT1yGdlZWHRokUYNmyYc7vy16vzj3/8AyqVyvn1+PHj0bJlS7z11lvIzs5GTEwMAOCll16CKIpYt26ds618fwBo3749OnbsiB9++AG33nprhfUW3An/N998c4VrAIBbbrkF48ePx5YtWzB69GiXj6VSqTBo0CBs2bIFzzzzDKRSKYCyD2T27dtX4f5MmjQJU6dOrbB/UlIS5s6diz///BM9evRw+bxV+fTTT3HhwgWsW7cOcXFxAIAJEyagcePGWLp0KaZOnYqmTZti+/bt0Gg0WLp0qbNmoprisH8iIiIiCmjPPvssPv300wr/eEpRURH27NmD4cOHO0cYFBQUoLCwEP3790dmZiZycnIAlC0mmJSU5Az+QFlv+B133OHSuYYPH46jR4/i/PnzzrZNmzZBoVDg1ltvBQBoNBoAwG+//Qaj0ejWtVwb/EtLS1FQUIDk5GSIoohjx44BKAvv+/btw1133VUh+APw+KKo19ZjtVpRWFiIFi1aQKvVOutxx/Dhw5Gfn19h6P+WLVvgcDhw++23X/e8ZrMZBQUF6Nq1KwDg6NGjNbmUSjZv3ozu3btDq9U6v2cKCgrQr18/2O127Nu3DwCg1WphNBqRmprqkfNSw8aefyIiIiIKaImJiV5bxPn8+fMQRRGLFi3CokWLrrtNfn4+oqOjkZ2d7QyR12rVqpVL5xo2bBhee+01bNy4EdOnT4coiti8eTMGDBjgDP3NmzfHgw8+iE8//RTff/89evTogUGDBuHOO++sdsg/AGRnZ+Odd97Bzz//7Fw/oJzBYAAAXLhwAQCcQ+S9yWQy4YMPPsDatWuRk5NT4YknN1q/4HoGDBiAkJAQbNy40bmGw8aNG9GhQ4cK70FRURGWLFmCjRs3Ij8/v8IxanLe6zl37hxOnjzprOPvykdITJo0CZs2bcIjjzyC6OhopKSkYPjw4RgwYIBH6qCGheGfiIiIiKiGyhdnmzp1Km666abrbtOiRQuPnCs6Oho9evTApk2bMH36dBw4cADZ2dnO4fbl5s2bhzFjxmDbtm1ITU3FSy+9hA8++ABr1qxBkyZNrntsu92OBx98EMXFxXj44YfRunVrBAUFIScnB/PmzXNpUUJXVDU6wG63V2p78cUXsXbtWkyePBlJSUkICQmBIAiYM2dOjR59Wj5CYuvWrXjuueeQn5+P/fv3Y+7cuRW2mz17NtLS0vDQQw+hQ4cOCAoKgsPhwMMPP1zjR67+/focDgdSUlIqrd9QrnwqQGRkJL799lv89ttv2LlzJ3bu3Im1a9di9OjReP3112tUCzVcDP9ERERERFdVFU6ram/evDmAssdE9+vXr9pjx8TE4Ny5c5Xaz54963J9w4cPxwsvvICMjAxs3LgRarUat9xyS6XtylfYf/zxx7F//35MnDgRq1atwpw5c6573FOnTiEzMxOvv/56hbn0fx9uXn695SvjV6Wq+xUaGgqgbKX7a2VnZ1fatnxe/7Wr5JvN5lr1vg8fPhzr1q3D7t27cebMGYiiiOHDhztfLy4uxu7duzFz5swK6wBkZma6dPzQ0NBK12axWJCbm1uhrUWLFigtLb3h9wxQ9qHFoEGDMGjQIDgcDjz//PP48ssv8fjjj6Nly5Yu1UUEcM4/EREREZFT+Qryfw9wVbVHRkaiV69e+PLLL3HlypVKx7t2gbuBAwfiwIEDOHToUIXXv//+e5frGzp0KKRSKTZs2IDNmzc7V7EvZzAYYLPZKuzTrl07SCQSWCyWKo8rkZTFgmt7tkVRxGeffVZhu4iICPTs2RPffPNNpcB+7b7l9+vvQV2j0SA8PBx//PFHhfaVK1dWqul6C9ytWLHiuqMEXNWvXz+EhYVh48aN2LRpExITE50faFR1TgAuP1qvefPmla5tzZo1lWoePnw40tLS8Ouvv1Y6hk6nc76Hf3+8oEQicT5lorr3k+h62PNPRERERHRVp06dAJStaN+/f39IpVKMGDECKpUKbdq0waZNmxAXF4ewsDDn4+Gee+45TJo0CXfccQfuueceNG/eHHl5eThw4AAuX76M9evXAwAefvhhfPfdd3j44YfxwAMPOB/1FxMTc92nD1xPZGQkevfujU8//RQlJSUVFqoDgD179uC///0vhg0bhri4ONjtdnz33XeQSqUYOnRolcdt3bo1WrRogddffx05OTnQaDTYsmVLpQ87AOCZZ57BxIkTMWbMGIwfPx7NmjXDxYsXsX37dnz33XcV7uPChQtx++23Qy6X45ZbbkFQUBDuvvtufPjhh/j3v/+Nzp07448//rju6Iebb74Z3333HTQaDdq0aYMDBw5g165dCAsLc+leXY9cLseQIUOwYcMGGI1G/N///V+F1zUaDXr27ImPP/4YVqsV0dHRSE1NRVZWlkvHv/vuu/Hcc89h5syZ6NevH06cOIHffvvN+bjDcg899BB+/vlnTJ8+HWPGjEGnTp1gNBpx6tQpbNmyBdu2bUNERASeeeYZFBcXo0+fPs51Iz7//HN06NAB8fHxNb4P1DAx/BMRERERXXXbbbfh/vvvx4YNG7B+/XqIoogRI0YAKPtA4MUXX8Srr74Kq9WKJ554Au3atUObNm3wzTffYMmSJVi3bh2KiooQERGBjh07YsaMGc5jN27cGJ999hleeuklfPjhhwgLC3M+3q38ue6uuP3227Fr1y4EBwdj4MCBFV5LSEhA//798csvvyAnJwdqtRoJCQn46KOPkJSUVOUx5XI53n//fef6AEqlEkOGDMG9995b6dGG7du3x5o1a7Bo0SKsWrUKZrMZMTExFYbPJyYm4sknn8Tq1avx66+/wuFwYNu2bQgKCsKMGTNQUFCALVu2YNOmTRgwYAA+/vjjSovf/fvf/4ZEIsH3338Ps9mMbt264dNPP61ynrw79++rr76CIAgVai63YMECvPjii1i5ciVEUURKSgo++uijKtd0uNY999yDrKwsfP311/j111/RvXt3fPrpp5UeN6lWq7FixQp88MEH2Lx5M7799ltoNBrExcVh5syZzsUZ77zzTqxZswYrV66ETqdDVFQUhg8fjpkzZzpHaxC5ShBrumpFgDt8+DAAeG1l2KqUlpbi+PHjzsVFAllDulaA1xvoGtL1NqRrBfzren31u4mIiIjqP35cRERERERERBTgGP6JiIioTp07dw7PPvssRo0ahY4dO2LkyJEu7SeKIj788EPcfPPNSExMxPjx43HgwAHvFktERBQgGP6JiIioTqWnp2PHjh1o2bKlWwtWffTRR3jnnXcwZcoUfPDBB4iKisLUqVNx4cIFL1ZLREQUGBj+iYiIqE4NGjQIO3bswDvvvONcEfxGzGYzPvjgA0ydOhVTpkxB37598dZbbyEsLAxLly71csVERET1H8M/ERER1amarFC9f/9+GAyGCitzKxQKDBkyBDt37vRkeURERAGJ4Z+IiIj8XkZGBoCyZ5FfKz4+HtnZ2TCZTL4oi4iIqN6Q+boAIiIiohvR6XRQKBRQKpUV2rVaLURRRHFxMVQqlVvHTEtLgyiKkMvlniyViIioxqxWKwRBQHJyssePzfBPREREDZIoihBFERaLxdelEBFRAyeKgEMUIREAQfDOAH2GfyLyGqlU6usSiChAaLVaWCwWmM3mCr3/Op0OgiAgNDTU7WPK5XJYLBbExcVBrVZ7stwGy2g0IjMzk/fUQ3g/PY/31LN4Pz1DV2pFidEKURShy7tYo7VxXMHwT0Q1Yii1oNRkq/J1q9UKQRGCQr0VBlOpW8cOUsmgCVLUtkQiCiDlc/3Pnj2L9u3bO9szMjIQExPj9pD/a6nVagQFBdW6RvoL76ln8X56Hu+pZ/F+1owoiigymOEQpVCpyjrNdIL3zsfwT0Q1Umqy4cS5Alhtjuu+brVYkHMlB9GNRcgVrgd5uUyC9i0jGP6JqIJu3bpBo9Fg06ZNzvBvtVrx448/YsCAAT6ujoiIyD3lwd9oskGso3My/BNRjVltjirDv8XmgMlig8XmACTX34aIGiaj0YgdO3YAAC5evAiDwYDNmzcDAHr16oWIiAhMnjwZ2dnZ2Lp1KwBAqVRi2rRpWLx4MSIiItCuXTusWrUKRUVFeOihh3x2LURERO5yOMqCv8lcd8EfYPgnIiKiOpafn48nn3yyQlv515999hl69+4Nh8MBu91eYZtHHnkEoijik08+QUFBATp06IClS5eiefPmdVY7ERFRbTgcIgr1ZpgsVU+f9RaGfyIiIqpTzZo1w8mTJ6vdZsWKFZXaBEHAtGnTMG3aNG+VRkRE5DV2h4givQkmi/3GG3sBwz8RERERERGRF9kdIop0Jpisvgn+AOCdZwgQERERERERkVvBX/TiIgAM/0REREREREReYLc7UOhi8C8xWqErsXitFr8a9n/u3DksXboUBw8eRHp6Olq3bo0ffvih2n2uXLmCZcuWITU1FefPn0dISAh69uyJuXPnIjY2to4qJyIiIiIiIvqL3e5Agc5U9vSrG9CXWrBodRru6qPxWj1+Ff7T09OxY8cOdO3aFQ6HA6ILYx6OHj2KrVu34q677kLXrl1RWFiI//3vf7j77rvxww8/ICIiog4qJyIiIiIiIipju9rj70rwLzaYsWh1GrLzSgA0kPA/aNAg3HrrrQCAefPm4ciRIzfcp3v37ti0aRNksr8upVu3brj55pvx7bffYurUqV6rl4iIiIiIiOhaVpsDRXrXgn+h3oS3V6Uhp6DU63X5VfiXSNxfgkCr1VZqa9KkCSIiInDlyhVPlEVERERERER0Q+4E/4JiExau2o/cIqOzTa30XkT3q/DvKWfPnkV+fj7i4+N9XQoRERERERE1AFabHYU6M6z2Gwf/3CIjFq7cjwKdydl254DWUCu99yjAgAv/oijipZdeQuPGjTFixIhaH6u01PvDL65lNBor/DuQNaRrBQLveq1WK6wWS5Wfalqt1gr/dplDAqvVWuc/e7UVaO9vdRrStQL+db2iKEIQBF+XQURERH9jsdpRqDfD5kLwzykoxcJV+1GkNzvbxt7SBrf1bomcrNNeqzHgwv/ixYuxZ88efPzxxwgKCqrVsaxWK44fP+6hytyTmZnpk/P6QkO6ViAwrlcqlUJQhCDnSg5MFlu12+bl57l1bJVChqbhAnIv6WG3e++TT28JhPfXVQ3pWgH/uV6FQuHrEoiIiOgaZcHfBJv9xgvWZ+cZ8PaqtAqP9Lvn1nYY1KO5N0sEEGDhf82aNXj33Xfx8ssvo2/fvrU+nlwuR5s2bTxQmeuMRiMyMzMRFxcHtVpdp+euaw3pWoHAu95CvRXRjcVqe/7z8vPQKLIR5HK5y8dVyCRoFNkI4SFNPVVqnQi097c6DelaAf+63tOnvdcbQERERO4zXw3+dheCf1aOHm+vToPB+NfI2HuHtcdNSXXziPqACf9bt27F888/j1mzZmHcuHEeOaYgCLUePVBTarXaZ+euaw3pWoHAuV6DqRRyhQKQVD+0SS6Xu9VTKZdJIJfL6+09CpT31xUN6VoB/7heDvknIiLyH2aLDYV6M+yOGwf/c5d1eGd1GkpMZaNmBQD3394B/RJjvFzlXwIi/O/duxdz587F3XffjRkzZvi6HCIiIiIiIgpg7gT/jIvFWLzmAIzmsuAvEQRMGdkRvTo18XaZFfhV+DcajdixYwcA4OLFizAYDNi8eTMAoFevXoiIiMDkyZORnZ2NrVu3AgDOnDmDGTNmIC4uDqNGjcKBAwecx4uIiECLFi3q/DqIiIiIiIgoMJksNhS5GPzTLxRiyVcHYbaUrWUlkQh46M5O6N4+2ttlVuJX4T8/Px9PPvlkhbbyrz/77DP07t0bDoejwiJgBw8ehF6vh16vx8SJEyvsO2bMGLz22mveL5yIiIiIiIgCntFsRbHB4lLwP5FZgPe+OQiLtWyarEwq4JHRXdC1bZS3y7wuvwr/zZo1w8mTJ6vdZsWKFRW+Hjt2LMaOHevNsoiIiIiIiKiBM5qtKNJb4BBvHPyPZuTj/bWHYLWVB38JHrsrEZ1aR3q7zCr5VfgnIiIiIiIi8jelprIef1eC/6HTefhw3SHno//kMglmjOuK9nER3i6zWgz/RERERERERFUoMVmhczH4p528go++OwLH1WkBSoUUT4zrirYtwr1d5g0x/BMRERERERFdh8Fogb7EAhem+GPfscv49Ptjzg8JVEopZt2TjNaxoV6u0jUM/0RERERERER/Yyi1QF/qWvDfc/gSlm88hvLBAUEqGZ4cn4yWTbXeLdINDP9ERERERERE19CXWKA3WuDCSH/8dvAivth0AuWbatRyPDkhGc2jQ7xao7sY/omIiIiIiIiu0hksMJhcC/7b/7yA1VtPOb/WBivw5IRkxEZpvFhhzTD8ExEREREREQEoNphRYrK6FPx/+v08vv453fl1qEaJOROT0SQy2IsV1hzDPxERERERETVooiiiuMSCUheD/+bdmfh2xxnn1+FaJeZM7IbG4UFerLJ2GP6JiIiIiIiowRJFEUUGM4wmG26U+0VRxA+/ncWG1LPOtkahKsye2A2NwtSeKUjwzGH+juGfiIiIiIiIGiRRFFGoN8Nkdi34f7vjDLbsOedsaxyuxuyJ3RChVXmkHkEQIBG8k/4Z/omIiIiIiKjBcTiuBn+L7YbbiqKIr39Ox7Z9F5xtTSKDMGdiN4RqlB6pRyopC/5eyv4M/0RERERERNSw2B0iivQmmCz2G27rEEV8ufUkduy/6GyLjdLgyQnJ0AYrPFKPTCogLESFK14K/gDDPxERERERETUgdoeIIp0JJqtrwf+LzSeQejDb2dYiOgSzJiRDo5Z7pB65VIJwrRJymdQjx6sKwz8RERERERE1CHa7A4V6M8yuBH+HiM82HsOeI5edba1itJh5TxKCVJ4J/gqZBGEhKshlEo8crzoM/0RERERERBTwbHYHCnUmWGyOG25rtzvw6Q/H8MfxHGdbm2ahmHF3EtRKz8RohUyCcK0KMqn3gz/A8E9EREREREQBzp3gb7M78PF3R3DgVK6zLaFFOB4blwiVwjMRWiWXIixECWkdBX+A4Z+IiIiIiIgCmNXmQJHeteBvtdnx4bojOHwmz9nWsVUEpo9NhELumTn5KoUUYSEqSCVeXN3vOhj+iYiIiIiIKCBZbXYU6syw2m8c/C1WO95fewjHzhY427rER+LRMV08thifSiFDeIgSkjoO/gDDPxEREREREQUgi9WOQr0ZNheCv8liw/++PoST5wudbUntovDwqM4emZMvAFCrZAjTKCEIdR/8AYZ/IiIiIiIiCjBmqx2FehPsdvGG2xrNNiz56gDOZBU723p0iMaDIzt6ZE6+PwR/gOGfiIiIiIiIAojZYkOhwexS8C8xWbH4ywPIvKRztvXp3AQP3N7RI0PzBQEIVskRqlHW+li1xfBPREREREREAcFssaFQb4bdcePgbzBasWh1Gi7k6J1tKV1jcO+w9pB4oIfen4I/wPBPREREREREAcBksaHIxeCvK7Fg0eo0XMw1ONsGdovF+CEJHgn+EgEICVJAE6So9bE8heGfiIiIiIiI6jWj2Ypig8Wl4F9sMGPhqv24nF/qbBvcsznGDWrrkTn5EkGAVqNAsEpe62N5EsM/ERERERER1VtGsxVFegsc4o2Df6HOhIWr9uNKodHZNrRPS4weGO+R4C+VCAgLUUKl8L+o7X8VEREREREREbmgxGSFzuBa8M8rMuLtVfuRV2xyto3s3wojUlp5JPjLpALCQlRQyqW1PpY3MPwTERERERFRvVNitEBXYoELI/1xpbAUb69KQ4Hur+A/emA8hvWN80gtcqkE4Vol5DL/DP4Awz8RERERERHVMwajBXoXg//l/BIsXJWGYoPZ2TZuUFvc2quFR2opC/4qyGUSjxzPWxj+iYiIiIiIqN7Ql1igN1rgwkh/XMw1YNHqNOhKLM62Cbcl4OZuzTxSi0ImQViI/wd/gOGfiIiIiIiI6gmdwQKDybXgfyFHj7dXp6HEaAUACADuHd4e/bvGeqSW+hT8AYZ/IiIiIiIiqgeKDWaUmKwuBf/MSzq882UaSk02AIAgAJNHdESfzk09UotCVjbUXyatH8EfYPgnIiIiIiIiPyaKIopLLCh1MfifySrC4q8OwGS2AwAkgoCpd3ZCjw7RHqmnPgZ/gOGfiIiIiIiI/JQoiigymGE02eBC7sep84V496uDMFvLgr9UIuDhUZ2RnNDYI/XU1+APMPwTERERERGRH3I3+B/PLMB7Xx+E1eYAAMikAh4dk4jENo08Uk99Dv4Awz8RERERERH5GVEUUag3w2R2LfgfPpOHD9Yehs1eFvzlMgmmj01Ep9aRHqlHIZMgQquCtJ4Gf4Dhn4iIiIiIiPyIw3G1x99sc2n7A6dy8dG3h2F3lH1MoJBL8PhdXdE+LsIj9QRC8AcY/omIiIiIiMhPOBxXe/wtrgX/P0/kYOn6o3BcDf4qhRRP3J2ENs3DPFJPoAR/gOGfiIiIiIiI/EBZ8DfBZLG7tP3eo5ex7IejzicAqJUyzBqfhFYxoR6pp3yOfyAEf4Dhn4iIiIiIiHzM7hBRpDPBZHUt+O86lI0VG4871wMIVskwa0IyWjbReqSe+r643/Uw/BMREREREZHP2O0OFOrNzsfz3cjOtCys3HLS+XVIkBxPTkhGs8YhHqknEIM/wPBPREREREREPuJu8P/ljwv48qdTzq+1wQrMnpiMmEYaj9Qjl0oQFhJ4wR9g+CciIiIiIiIfsNkdKNSZYLE5XNr+x73nsPaX086vw0OUmD2xG6IjgjxSj1QqIFyrhFwWeMEfYPgnIiIiIiKiOma1OVCkdz34b0w9i/W/Zji/jtCqMHdSNzQKU3ukHqlEQLhGCblM6pHj+SOGfyIiIiIiIqozVpsdhTozrPYbB39RFPH9rxnYuCvT2RYVpsacid0QEarySD0SQUBYiBJKRWDH48C+OiIiIiIiIvIbFqsdhXozbC4G/7XbT2Pr3vPOtuiIIMyemIzwEE8GfwVUAR78AYZ/IiIiIiIiqgNmqx2FehPsdvGG24qiiDU/ncIvf2Y522IaBWP2xGRog5UeqUciANpgOdRKuUeO5+8Y/omIiIiIiMirzBYbCvVm2B03Dv4OUcSqLSfx64GLzrZmjTV4ckIyQoIUHqlHEACNWoFgtWeOVx8w/BMREREREZHXmCw2FLka/B0iPt90HLsOX3K2tWwSglnjkxGs9kwPvSAAGpUCIcENJ/gDDP9ERERERETkJUazFcUGi0vB3+5wYPmG4/j96GVnW+vYUMy8OwlqlWeiqwAgSCWHVtOwgj/A8E9EREREREReUGKyQmewwCG6EPztDiz9/ij2n7jibGvbPAwzxnWFSum54K9WyRDawHr8yzH8ExERERERkUeVGC3QlVjgQoc/rDYHPv7uMA6m5znbElqG4/G7ukKpkHqsJpVShjCNEoIgeOyY9QnDPxEREREREXmMvsQCg9G14G+x2vHBusM4mpHvbOvUOhLTxnSBQu7B4K9o2MEfYPgnIiIiIiIiD9EZLDCYLHBhpD8sVjve++YQTmQWONsS2zTCI6O7QC6TeKwmlUKG8BAlJJKGG/wBhn8iIiIiIiKqJVEUUVxiQanJ6lLwN5ltePfrg0i/UORsS06IwkN3doZMyuDvDQz/REREREREVCtFBjOMJhtcyP0wmmxY/NUBZFwsdrb17BiNKSM7QirxZPCXMvhfg+GfiIiIiIiIakQmk6HIYAEEmUvBv8RkxTtfHsC5SzpnW98uTXH/8A4eDellwV/F4H8Nz32sQkREROSCM2fO4MEHH0RSUhJSUlIwf/58WCyWG+5XWFiIZ599FjfffDOSkpIwcuRIrFq1qg4qJiKi6xFFoMQswmiyuhT8DaUWvL1yf4Xgf1NSLO6/3XPBXwCgVsoY/K+DPf9ERERUZ4qLizF58mTExcVh8eLFyMnJwWuvvQaTyYRnn3222n2ffPJJZGRkYO7cuWjatCl27tyJ559/HlKpFPfcc08dXQEREQGA3e5Aod4MQ6kZjV3YXldixtur0pCdV+Jsu6V7M9xzazuPrcAvAFCruKp/Vfwq/J87dw5Lly7FwYMHkZ6ejtatW+OHH3644X6iKOKjjz7CypUrUVBQgA4dOuDpp59GUlKS94smIiIil61evRolJSVYsmQJwsLCAAB2ux0vvPACpk2bhujo6Ovul5ubi7179+LVV1/F2LFjAQB9+/bF4cOHsWHDBoZ/IqI6ZLM7UKgzwWSxQXRhdb9CvQlvr0pDTkGps21I7xYYe3MbzwV/oazHn8G/an417D89PR07duxAy5YtER8f7/J+H330Ed555x1MmTIFH3zwAaKiojB16lRcuHDBi9USERGRu3bu3Im+ffs6gz8ADB8+HA6HA6mpqVXuZ7PZAAAhISEV2jUajUt/eBIRkWdYbXYU6kyw2BwubV9QbMJbX+yvEPxv7xfn8eAfrJIjPETF4F8Nv+r5HzRoEG699VYAwLx583DkyJEb7mM2m/HBBx9g6tSpmDJlCgCge/fuGDZsGJYuXYrnn3/eixUTERGROzIyMnDXXXdVaNNqtYiKikJGRkaV+zVt2hT9+/fH+++/j1atWqFJkybYuXMnUlNT8eabb9aqJqPRWKv96S/l95L31DN4Pz2P97R2bHYHCg0WWK12AIDZZK7w77/LLzbhvbVHUaD76/XhfZtjSM8YmEwmj9QkCAI0ajnkEglKS0tvvIOfE0XRax9g+FX4l9TgsQ779++HwWDA8OHDnW0KhQJDhgzB1q1bPVkeERER1ZJOp4NWq63UHhoaiuLi4uvs8ZfFixdjzpw5GDFiBABAKpXimWeewdChQ2tVU2ZmZq32p8p4Tz2L99PzeE/dI5FIAEEKXakNJnPlBVqzLmZVaisy2PDtnkIYTH+NEOjXQYP4SAvOnDnjkbqkUilCgpQwyEVkXR0hFggUCoVXjutX4b8mynsJWrduXaE9Pj4ey5cvh8lkgkql8kVpRERE5CGiKOLpp59GZmYmFixYgKioKOzatQuvvPIKQkNDnR8I1ERcXBzUarUHq224jEYjMjMzeU89hPfT83hPa8ZkcUBXYkaIveJQf7PJjKyLWWgW2wxKldLZfjm/FMt/Ploh+I8eEIeByTEeq6m8xz8kSO6xY/qD9PR0rx273od/nU4HhUIBpVJZoV2r1UIURRQXF9c4/IuiWOdDRxrSUKSGdK1A4F2v1WqF1WKpcr6X1Wqt8G+XOSSwWq31bthWoL2/1WlI1wr41/V6cyhgXdFqtdDr9ZXai4uLERoaWuV+27dvx+bNm7F+/XokJCQAAHr37o38/Hy89tprtQr/arUaQUFBNd6fKuM99SzeT8/jPXVdidECs80KuUKJqmK2UqV0fpiSdUWP99Yehb70r78BJw1NwIDkZh6rqXyOf6hGeeON6xlv/p6v9+Hfm6xWK44fP+6TczekoUgN6VqBwLheqVQKQRGCnCs5MFmqH2KVl5/n1rFVChmahgvIvaSH3W6vTZk+EQjvr6sa0rUC/nO93hoKWFdat25daW6/Xq9Hbm5upVF81zp9+jSkUinatWtXob1Dhw746quvYDQa2YtHRORh+hILDEYLHC6uq3r+sg6LVqehxFT296EA4P7bO6Bfoid7/AM3+HtbvQ//Wq0WFosFZrO5Qu+/TqeDIAjV9iLciFwuR5s2bTxRpssa0lCkhnStQOBdb6HeiujGYrU9/3n5eWgU2QhyuevDsRQyCRpFNkJ4SFNPlVonAu39rU5DulbAv6739OnTPj2/JwwYMADvv/9+hbn/mzdvhkQiQUpKSpX7xcbGwm634+TJk2jfvr2z/ejRo4iMjPT5e0NEFGh0BgsMJgtcfaDK2exiLP7yAErNV4O/AEwZ0RG9O3vubzoG/9qp9+G/vJfg7NmzFf4YyMjIQExMTK3m+wuC4LPhQA1pKFJDulYgcK7XYCqFXKEAJNU/5kUul7vVUymXSSCXy+vtPQqU99cVDelaAf+43vo+5B8AJkyYgBUrVmDGjBmYNm0acnJyMH/+fEyYMAHR0dHO7SZPnozs7Gzn4r0DBgxATEwMZs2ahRkzZqBx48b47bffsG7dOsycOdNXl0NEFJCKDWaUmKwuB/+MbB0++u44TJayUZsSiYCpd3RCjw7RN9jTdYIAaFQKaDX1ewScL9X78N+tWzdoNBps2rTJGf6tVit+/PFHDBgwwMfVERER0bVCQ0OxfPlyvPjii5gxYwaCg4Mxbtw4zJkzp8J2DoejwtQfjUaDZcuWYeHChXjzzTeh1+vRrFkzzJs3D/fdd19dXwYRUcByN/hn5Vmw8c9jsFjLOoSkEgGPjO6CpHZRHqtJEIAQtQIhwQz+teFX4d9oNGLHjh0AgIsXL8JgMGDz5s0AgF69eiEiIqJST4BSqcS0adOwePFiREREoF27dli1ahWKiorw0EMP+exaiIiI6Pri4+OxbNmyardZsWJFpbaWLVvi7bff9k5RREQNnCiKKC6xoNSN4H/yXBF++L0Q5bNAZVIJpo3tgi7xjTxWF4O/5/hV+M/Pz8eTTz5Zoa38688++wy9e/eu1BMAAI888ghEUcQnn3yCgoICdOjQAUuXLkXz5s3rrHYiIiIiIqL6SBRFFBnMMJpscDH34/DpPHz8/XFn8JfLJHh8XFd0iIvwWF0SAQgJUkATxODvCX4V/ps1a4aTJ09Wu831egIEQcC0adMwbdo0b5VGREREREQUcERRRKHeDJPZ9eCfdvIKPv7uCOxXHwOgkEvwxN1JaNci3GN1SQQBWo0CwSrXF46m6vlV+CciIiIiIqK64XCUBX+zxfXg/8fxHHyy/igcV+cGKGQCpo/u6NHgL5UICNUooFYy+HsSwz8REREREVEDUxb8Tc4V+l2x98glLNtwzLkmgFopxcieoWgVo/VYXVKJgPAQJZQKRlVP4x0lIiIiIiJqQOwOEUU6E0xW14N/6sFsfL7puHOEQLBajsfGdIRJd9ljdcmkAsJCVFDKpR47Jv1F4usCiIiIiIiIqG7Y7Q4Uuhn8d+zPwoprgn9IkBxzJ3VDbFSwx+qSSyWI0DL4exPDPxERERERUQNgsztQoDPB7Ebw37bvPFb9+Nei7KEaBZ66tztiozQeq0shkyBcq4JcxuDvTRz2T0REREREFOCsNgeK9CZYyp/N54ItezKxbvsZ59fhWiVmT+iG6Iggj9VVHvxlUvZLexvDPxERERERUQCz2uwo1JlhtbsW/EVRxMZdmfj+1wxnW2SoCnMmdkOjMLXH6lLKpQgPUULK4F8nGP6JiIiIiIgClMVqR6HeDJsbwf+7nRnYvDvT2RYVrsacid0QoVV5rC6VXIowrQpSieCxY1L1GP6JiIiIiIgCkNliQ6HBDLtdvPHGKAv+3/xyGj/9ft7Z1iQyCHMmdkOoRumxuhj8fYPhn4iIiIiIKMCYLDYU6c2wO1wL/g5RxJqtp7B9f5azLTZKgycnJEMbrPBYXSqFFGEhDP6+wPBPREREREQUQIxmK4oNFreC/6otJ/DrgWxnW4voEMyakAyNWu6xulQKGcJDlJAw+PsEwz8REREREVGAKDFZoTNY4BBdDP4OEZ9tPI49Ry452+KaajFrfBKCVJ4J/gIAJYO/zzH8ExERERERBQCD0QJ9iQUudvjDbnfg0x+O4Y/jOc62+GaheOLuJKiVnomKggColTKEaZQQBAZ/X2L4JyIiIiIiquf0JRbojRa42OEPm92Bpd8dQdqpXGdbQotwPDYuESqF54J/sEru0cUCqeYY/omIiIiIiOoxncECg8n14G+12fHhuiM4fCbP2dYhLgKP3ZUIhVzqkZokAqBRKxDiwcUCqXYY/omIiIiIiOqpYoMZJSary8HfYrXj/bWHcOxsgbOtS3wkHh3TBXKZp4K/AK1GgWAPrRlAnsHwT0REREREVM+IoogigxlGs83l4G+22PHeNwdx8lyhs61r2yg8MrozZFKJR+qSCAJCNQqPLRZInsPwT0REREREVI84g7/JBhdzP0xmG5Z8dRCns4qcbd3bN8bUOzpB6sHgHxaigFrJ4O+PGP6JiIiIiIjqCYejLPibzK4H/1KTFYvXHMDZbJ2zrXenJnhgRAdIJQz+DQXDPxERERERUT3gcIgo1Jtgsthd3qfEaMWiL9Nw/rLe2dYvsSnuG9YBEolnHr0nlTD41wcM/0RERERERH7O7hBRpDPBZHU9+OtLLVi0Og1ZVwzOtgHJsZhwWwIkgmeCv0IhR6hGxeBfDzD8ExERERER+TG73YFCvRlmN4J/scGMt1en4VJeibNtUI/muHtwWwgeCv4yqQShwXKoFJ6ZOkDexXeJiIiIiIjIT1ltDhToTG4F/0K9CW+t3F8h+A/t09KjwV8qERCqUUIQXa+LfIs9/0RERERERH7IarOjUGeG1e5weZ/8YiMWrkpDXpHR2TYipRVG9m/l0eAfFqKEw2aBw+F6beRbDP9ERERERER+xmy1o1Bvgt3u6pr+QG5hKRauSkOBzuRsGzUgHsP7xXmsLqlEQHiIEkqFDKU2i8eOS97H8E9ERERERORHzBYbCvVm2B2uB//L+SV4e3UaivRmZ9u4QW1xa68WHqvr2uBP9Q/fNSIiIiIiIj9Rk+CfnWvA26vToCv5qyd+/JB2uKV7c4/VxeBf//GdIyIiIiIi8gMmiw1Fbgb/rBw93l6dBoPRCgAQAEwa1h43JcV6rC4G/8DAd4+IiIiIiMjHjGYrigwWONwI/ucu67BodRpKTTYAZcH//ts7oF9ijMfqYvAPHHwHiYiIiIiIfKjUZEWxwQKH6Hrwz7hYjHfWpMFkLnvUnkQQMGVkR/Tq1MRjdTH4Bxa+i0RERERERD5iMFqgL7HAjQ5/pF8oxJKvDsJsuRr8JQIevrMzurVv7LG6GPwDD99JIiIiIiIiH9CXWKA3WuBGhz9OZBbgvW8OwmJ1AABkUgGPju6CxLZRHqtLKhEQxuAfcPhuEhERERER1bFigxklJqtbwf9oRj7eX3sIVltZ8JfLJJg+NhGdWkd6rC6JICBUo4CKwT/g8B0lIiIiIiKqI6IooshghtFscyv4H0rPxYffHobNXraTQi7B43d1Rfu4CI/VVh781Uq5x45J/oPhn4iIiIiIqA6IoohCvRkmsw1u5H6knbyCj7474nwSgFIhxRN3d0Xb5uEeq00iAFqNAkEqBv9AxfBPRERERETkZQ7H1eBvsbm1375jl/Hp98ecTwJQK2WYeU8SWseGeqw2iSBAq1EgmME/oDH8ExEREREReZHdIaJIb4Lp6ur8rtp9+BI+23jMOT0gSCXDkxOS0bKJ1mO1lQ/1Z49/4GP4JyIiIiIi8hK73YFCvRlmq3vB/9cDF7Fy8wnn9ACNWo7ZE5LRLDrEY7Ux+DcsDP9EREREREReUNPg/8ufF/Dl1lPOr7XBCsyekIyYKI3HapMIAsJCuLhfQ8LwT0RERERE5GE2uwOFOhMsVx/L56qte8/hm19OO78OC1FizsRuiI4I8lhtDP4NE8M/EdWKKIrIvKTD8cwCWKwOSASgdWwoWsd47pNpIiIiovrEanOgSO9+8N+0KxPf7Tzj/DpCq8KcicmICmfwp9pj+CeiGivSm7Fh11nkFhortF+4YsC+YzJ0iVOiaRMfFUdERETkA1abHYU6M6x214O/KIr44bez2JB61tnWKEyNOROTERmq9lht5Y/zY/BvmBj+iahGLuWV4Kttp1BiskEmlaBLfCSiwtUwlFpx6HQeDEYr9p2yITRUj7YtIn1dLhEREZHXWax2FOpNsNnFG298lSiK+HbHGWzZc87ZFh0RhNkTkhGuVXmsNolQtnYAH+fXcDH8E5HbLueXYP7nf6DEZEOEVoU7b2qNYPVfv0gS2zTC5t2ZyLysx0/7sqBSKtDcgyvTEhEREfkbs8WGQr0Zdod7wf+rben4+Y8LzramjYIxe0IyQjVKj9UmCEBIkALBaoXHjkn1j8TXBRBR/WK3O/DWyv3QlVjQKEyN0QPjKwR/AJBKJRjcIxZNI+RwiMC2fedhsth8VDERERGRdxnNVreDv0MUserHkxWCf2yUBnMndfN88FcroAli8G/oGP6JyC1f/5KO45kFUCmkuKN/K6iV1x9AJJEISGoVhNBgBUpMNuxMu1jHlRIRERF5X6nJiiK9xb3g7xDxxaYTFf4+ahEdgjmTuiHEgyG9PPiHBDP4E8M/Ebnh3GUdVm05CQC4d2j7G34qLZUKuLlbDAQBSL9QhIzs4rook4iIiKhOGIwWFBvMcIiuB3+7w4HlG44h9VC2s61VjBazJyZDo/bcfHwGf/o7hn8ictnyDcdgd4jo3akJ+nZp6tI+jcPVSG7XGACw5/Alt345EhEREfkrfYkFuhIL3Ojwh93uwKffH8Xeo5edbW2aheLJ8ckI8uBCfAz+dD0M/0TkkiNn8rDvWA4kEgFTRnaEIAgu79utfWMoFVIU6s04ea7Qi1USEREReZ/OYIHeaIE7fRo2uwMffXcEfxy/4mxLaBmOmfckQ1XFNMqaEARAo2Lwp8oY/onohkRRxLIfjgEAhvZuiWaN3Vu5XymXontCWe//78cuw+7Gc2+JiIiI/EmxwQyDyb3gb7XZ8cHaQzhwKtfZ1ql1JGaM6wqlQuqx2sqDv1bD4E+VMfwT0Q2lnczFyfOFUCqkmHhbQo2O0aVNIwSr5TCUWnHyPHv/iYiIqH4RRRFFBjNKTFa3gr/Fasd7Xx/C4TP5zrbENo0wfWwiFHLPBv9glZzBn6rE8E9EN/TtjtMAgKF9WiJcq6rRMWRSCbq2bQQAOJieB5Fz/4mIiKieKA/+pUb3gr/JYsOSrw7geGaBsy05IQqPjukCucxzUUwAEKSSe/QRgRR4GP6JqFqZl3RIO5ULiQDc0b91rY7VMS4SMqkEBToTLuYaPFQhERERkfeUB3+jyQZ3ui6MZhsWrzmAU+eLnG09OkTj4VGdIZN6NvirVTKEco4/3QDDPxFV67sdZwAAfRNj0CQyuFbHUiqk6BAXDqCs95+IiIjInzkcIgr17gf/EpMVi1an4UzWX4857tO5Kabe0QlSiWcjmEopQ5hG6dZizNQwMfwTUZWKDWZs358FABg9MN4jx+zSpmzof+YlHYoNZo8ck4iIiMjTyoK/CUaze8HfUGrB26vSkHlJ52zr3zUGD4zoAInEswFdpZAhPITBn1zD8E9EVfrlzwuw2R1o0zwM7VtGeOSY4SEqNI/WAABO8LF/RERE5IfsDhGFOhNMFrtb++lKzFi4Kg0XcvTOtoHdmmHSsPaQeDigqxRSBn9yC8M/EV2XKIr4ce95AMBtvVp49NjlHyScPFfIhf+IiIjIr9jtjrLgb3Uv+BfpzXhr5f4K6xrd2rMFJgxp5/ngL5ciLETl8ZEEFNgY/onouk6eL8SFHD0UcikGJDfz6LFbx4ZCIZNAX2pBdm6JR49NREREVFNWmwMFOhPMbgb/Ap0JC1b+icv5pc62YX3jcNegNh7vmVfKpQjTqiBl8Cc3+V34P3PmDB588EEkJSUhJSUF8+fPh8ViueF+hYWFePbZZ3HzzTcjKSkJI0eOxKpVq+qgYqLAtPVqr39KYlMEq+UePbZMKkGb5mEAgBPnCqrfmIiIiKgOWKx2FOpMsNgcbu2XV2TEgi/+RG6h0dl2R/9WGDWgtceDv0ImQXiIksGfakTm6wKuVVxcjMmTJyMuLg6LFy9GTk4OXnvtNZhMJjz77LPV7vvkk08iIyMDc+fORdOmTbFz5048//zzkEqluOeee+roCogCg8liw68Hyhb6G9K7pVfO0b5lBI6dLcDprGLclGyHQib1ynmIiIiIbsRssaHQYIbd7t50xCuFpVi4aj8KdX8tYjzm5ngM7RPn4QqvBn+tClIPPiaQGha/Cv+rV69GSUkJlixZgrCwMACA3W7HCy+8gGnTpiE6Ovq6++Xm5mLv3r149dVXMXbsWABA3759cfjwYWzYsIHhn8hNfxzPgdFsR+OIIHRuHemVczSJDII2WAFdiQXnLunQtnm4V85DREREVB2TxYYivRl2h3vB/3J+CRau2o9iw1+jlO8e3BaDe3p2rSSgLPiHhaggY/CnWvCr756dO3eib9++zuAPAMOHD4fD4UBqamqV+9lsNgBASEhIhXaNRsPFxIhqYGfaRQDAgKRYr60gKwgC2jQLAwCcvuYZuERERER1xWi2olDnfvC/mGvAgi/+rBD8J96W4JXgL5eWBX+5zK+iG9VDfvUdlJGRgdatW1do02q1iIqKQkZGRpX7NW3aFP3798f777+P06dPw2AwYOPGjUhNTcW9997r7bKJAkqJ0Yo/jucAAAYkx3r1XG2ahQIAzl3SwWJzb2EdIiIiotooMVpQpLfA4WZn4fnLery1cj/0pVYAgADg/uEdMLCbZxdIBgCZVEC4VsngTx7hV8P+dTodtFptpfbQ0FAUF1ffM7h48WLMmTMHI0aMAABIpVI888wzGDp0aI3rEUURpaWlN97Qg4xGY4V/B7KGdK1A/bnenWnZsNociI0KRuNQWZU/A1arFVaLpcpFcaxWa4V/X482SAptkBy6UivOXChEfKwWcEhgtVrr/GevturL++sJDelaAf+6XlEU+TxnIqJakkqlKDXZYHU44GaHPzIv6fDO6jSUmstGHgsCMGVER/Tu3NQLdQoID1FBznWRyEP8KvzXlCiKePrpp5GZmYkFCxYgKioKu3btwiuvvILQ0FDnBwLuslqtOH78uIerdU1mZqZPzusLDelaAf+/3h935wEA2jaR4sSJE9fdRiqVQlCEIOdKDkwWW7XHy8vPq/b1qFAJdKXAsYwrCJKWQKWQoWm4gNxLetjt9W80gL+/v57UkK4V8J/rVSgUvi6BiKhes9ol0JVaoFSq3NrvTFYRFq85AJOl7O8TiSBg6p2d0KPD9dclqw2pREC4RgmFnMGfPMevwr9Wq4Ver6/UXlxcjNDQ0Cr32759OzZv3oz169cjISEBANC7d2/k5+fjtddeq3H4l8vlaNOmTY32rSmj0YjMzEzExcVBrVbX6bnrWkO6VqB+XK/BaMXZnLL5/qNu6YyYqOAqty3UWxHdWKy25z8vPw+NIhtBLq/6UYFylRFnLmUiV2dDo0bRCFbJ0CiyEcJDPP8JujfVh/fXUxrStQL+db2nT5/26fmJiOo7vdEKXYkZ4W52+Z86X4h3vzoIs7Us+EslAh4e1RnJCY09XqNUIiA8RAmlwq+iGgUAv/qOat26daW5/Xq9Hrm5uZXWArjW6dOnIZVK0a5duwrtHTp0wFdffQWj0VijP9gEQUBQUJDb+3mCWq322bnrWkO6VsC/r3fPsQuwO0S0bBKCNi2jqt3WYCqFXKEAJNU/C1cul1fbU9k0Su5c9T+nyIyEFkGQy+V+e49uxJ/fX09rSNcK+Mf1csg/EVHNiKKIIoMZhlIrbG6OLDyeWYD3vj4I69UOD5lUgmljuqBLm0Yer1MiCAjVKBj8ySv8auWIAQMGYNeuXdDpdM62zZs3QyKRICUlpcr9YmNjYbfbcfLkyQrtR48eRWRkpM97aojqiz1HLgEA+nhh3lpVBEFAXNOytT4ys3U32JqIiIjIPQ6HiEK9GUaTze0ngR0+k4d3v/or+MtlEjw+LtGrwV+trHrEJFFt+FX4nzBhAoKDgzFjxgz89ttv+OabbzB//nxMmDAB0dF/zaWZPHkyhgwZ4vx6wIABiImJwaxZs/Ddd99h9+7deOONN7Bu3Trcd999vrgUonrHbLVj/8krAIA+Xep2yH2rmKvh/5IODndX3iEiIiKqgt0holBvgtFsg7t/YRw4lYv3vzkEm70s+CvkEjxxd1d0bBXp8TolAqANliNIxeBP3uNX4T80NBTLly+HVCrFjBkzsGDBAowbNw7z5s2rsJ3D4aiwEJhGo8GyZcvQsWNHvPnmm3jsscewY8cOzJs3D9OmTavryyCql9JOXoHZYkfjcDXiY6teY8MbmjbSQCGXwGi24XJB/Vrln4jcd+bMGTz44INISkpCSkoK5s+fD4vFcuMdAeTk5OD//u//0KdPHyQmJmL48OFYv369lysmovrIbnegUGdyLtDnjj9P5ODDbw/DfrVTQqWQYtY9yUhoGeHpMiEIQEiQAsFqLuhK3uV3k0ni4+OxbNmyardZsWJFpbaWLVvi7bff9k5RRA3A7sN/Dfmv63nFUomAlk20SL9QhIyL1T/Wk4h8RxRF7NmzBxaLBd27d4dGo3H7GMXFxZg8eTLi4uKwePFi5OTk4LXXXoPJZMKzzz5b7b5XrlzB+PHj0apVK7z44ovQaDRIT093+YMDImo4rDYHivSmKhcmrs7eI5ewbMMxlM8QUCtlmDU+Ca1iPN85IghAiFoBTRCDP3mf34V/Iqp7doeIfcdyANTtfP9rtYph+CfyJwsXLsT+/fudH7iLooipU6diz549EEURMTExWLZsGVq0aOHWcVevXo2SkhIsWbIEYWFhAAC73Y4XXngB06ZNqzDN7+/eeOMNNGnSBB9//DGk0rLHX/Xt27dmF0hEActitaNIb4bV7n7w33UoGys2HndOEQhWyfDkhGS0aKL1bJEoC/4alQIhwQz+VDf8atg/EflG+oVC6EstCFbJ0LGV54ezuaJFtBaCABToTMgtMvqkBiL6y5YtW5CYmOj8evPmzdi9ezdmz56NDz74AHa7HYsXL3b7uDt37kTfvn2dwR8Ahg8fDofDgdTU1Cr3MxgM2LRpEyZNmuQM/kREf2e22FCgN9Uo+O9My8Jn1wT/kCA55k7q7rXgH6ySQ6th8Ke6w/BPRPjjeFmvf1JCY0ilvvnPglIhRZPIYADA0TN5PqmBiP6Sk5ODli1bOr/eunUr2rRpg2nTpmHgwIGYOHEifv/9d7ePm5GRUenxvVqtFlFRUZUe93uto0ePwmq1QiaT4b777kOnTp2QkpKCN954A1ar1e06iCjwGM1WFOrNsNvdXzx4277zWLnlryeHhWoUmDupO2Ibuz+96UYElAX/UI3S48cmqg6H/RMR/jxRtsp/j/ZVD7etCy2iQ3AprwRHMvJxj08rISKZTOacSy+KInbv3o3Ro0c7X4+MjERhYaHbx9XpdNBqK/eihYaGori46mk/eXllHwo+88wzuOeee/DEE0/g0KFDeOeddyCRSPDUU0+5XUs5o5GjjTyl/F7ynnoG76frTGY7ikvMzgX6qmI2mSv8GwC2/XERP6Sec34dplHg8bGdEBYs8fi9L+/xl0skKC2t/4sc83vU80RR9Nr6Wwz/RA1cod6E0xeKAADd2zf2aS0tmoRg79HLOJ5ZAKvNAbmMg5OIfKVt27ZYv3497rjjDmzduhVFRUUYOHCg8/Xs7GyEh4fXWT0OR9kQ3n79+jmfAtSnTx+UlJTgk08+wYwZM6BSqWp07MzMTE+VSVfxnnoW72fVpFIpbA4JdKUWWK02l/fLupgFANiXbsDekyXO9hC1BHf20kJXkA1dgWdrlUgkCAlSwqAALtpcr7U+4PeoZykU3pkOwvBP1MClnSzr9Y9vFopwbc3+cPaUqDA11EoZjGYbTpwrQJf4Rj6th6ghmzFjBqZPn44+ffoAALp16+b8/wCwY8cOdOnSxe3jarVa6PX6Su3FxcUIDa16Je3y0QLX1gCULfj3/vvv49y5c0hISHC7HgCIi4uDWq2u0b5UkdFoRGZmJu+ph/B+3liJyQZ9qQVhN+jxL2c2mZF1MQuxMbH4Oe1KheDfKFSFx8d2QrjW88PxBQEIUsoRGmBz/Pk96nnp6eleOzbDP1ED98fxsvDf3cdD/gFAEAS0bBKCE+cKkXbyCsM/kQ+lpKRg3bp1SE1NhVarxe233+58rbi4GD169MDgwYPdPm7r1q0rze3X6/XIzc2ttBbAtdq0aVPtcc1mc7WvV0etViMoKKjG+1NlvKeexftZmSiK0JVYYHU4oFS613khiiJ+/OMyftmf7WxrEhmE2RO6ISzEO/PwVQoZwkOUkEjq9nHKdYXfo57jzUduc0wtUQNmtzucPf++nu9frmXTst698nUIiMh32rRpg8mTJ2PMmDFQKv/6gzg0NBT/+te/0Lt3b7ePOWDAAOzatQs6nc7ZtnnzZkgkEqSkpFS5X2xsLNq1a4ddu3ZVaN+1axdUKtUNPxwgosAhiiKKDGaUGK0Q3VzbTxRF/HpUXyH4x0QFY+4kbwZ/aUAHf6o/GP6JGrCT5wthMFoREiRHu5Z1N3e3Oi2bhAAAMi4Wo1Bv8nE1RHTgwAF88MEHeOWVV5xzOo1GI44ePYqSkpLqd76OCRMmIDg4GDNmzMBvv/2Gb775BvPnz8eECRMQHf3Xh5CTJ0/GkCFDKuw7Z84c/Pzzz3j55ZeRmpqK999/H5988gmmTJnCHieiBsLhEFGoN8NossHdNf0dooivfs7Aocy/Fqdr3liDuRO7QRvspeAvlyIsRMXgT36Bw/6JGrDy3vXkdo0h9ZNfSkEqOVo2CcG5y3qknczFoB7NfV0SUYNksVgwd+5cbNu2zbny8C233IK4uDhIJBJMnToVU6ZMwWOPPebWcUNDQ7F8+XK8+OKLmDFjBoKDgzFu3DjMmTOnwnYOhwN2u71C26BBg/DWW2/hvffew6pVq9C4cWPMnDkTjz76aK2vl4j8n90hokhvgsliv/HGf+NwiPh803HsPpLjbGvZJASzxicjWC33ZJlOSrkUYVqV3/yNRcTwT9SA/XG87Bdg9w7+MeS/XOfWja6G/ysM/0Q+smjRImzfvh3PP/88evfujWHDhjlfUyqVGDZsGLZt2+Z2+AeA+Ph4LFu2rNptVqxYcd3222+/vcL6A0TUMNjtDhTqzTBb3Q/+docDy344hn3H/gr+cU1D8OT4blCrvBOHFDIJwkOUDP7kVzjsn6iBKtCZkHGx7Jna3RJ8+4i/v+sUHwkA2H/yChwurt5LRJ61YcMGTJgwAePHj7/uKvzx8fG4cOGCDyojoobGZnegQGeqWfC3O7D0u6MVgn9MhBzTRnf0bvDXqiCVMmqRf+F3JFEDtf9E2S/Bts3DvLbATU3Fx4ZCrZRBV2LBmYtFvi6HqEHKz8+v9tF5UqkUJhPX5SAi77La7CjUmWCxOWqwrwMfrDuM/Sf/WkS4bfNQ3NErHCqF1JNlOpUHfxmDP/khflcSNVB/nPCfR/z9nUwqQVK7KACo8AubiOpO06ZNKz2S71r79+9HixYt6rAiImpozFY7CmoY/C1WO95fewiHTuc52zq1jsTDd7aHXOadofhyqQRhIQz+5L/4nUnUADkcIg6l5wLwvyH/5ZKv1rWfj/wj8omRI0di9erVSEtLc7aVP3t4zZo12LRpE0aPHu2j6ogo0JktNhTqTLDZ3Z/+Z7bY8d7XB3E0I9/Z1rVtI0wfmwiFzDs9/jKpBOFaJeQyxivyX1zwj6gBysguhr7UCrVShnYtwnxdznWVfyhx4lwhSk1WBKm8sxIvEV3f9OnTcfDgQdx3331o3bo1BEHAq6++iuLiYly+fBkDBw7ElClTfF0mEQUgo9mKYoMF9hqs+2My2/Du1weRfqHI2datfWM8dEcnSKUS2KweLPQqqVRAeIgSci99sEDkKQz/RA3QwVNlvf5d4hv57WI00RFBaNooGJfySnDkTD56dWri65KIGhSFQoGPP/4Y69evx5YtW+BwOGCxWJCQkIDZs2dj1KhRzpEARESeUmKyQmewwCG6H/yNJhsWf3XAuaAxAPTq1ASTR3SAVOKdv3ekEgHhISoo5Az+5P8Y/okaoINXh/x3bdvIx5VUL6ltFC7lleBAei7DP5EPCIKAUaNGYdSoUb4uhYgaAEOpBfpSC2ryoJ8SoxXvfJmGc5f1zrZ+XZrivuEdIPHS4/bKgr8SSgZ/qidq9RHYww8/jO+//56r/RLVI1abHUfPFgAAuraN8nE11Stf9O/AKc77JyIiCmQ6gwW6GgZ/fakFC1ftrxD8ByTH4r7b6yD4K9iXSvVHrb5bL1y4gP/3//4fgoKCMGTIEIwaNQp9+/blMEAiP3YisxAWqx1hIUq0aBLi63KqldimESQCcCHHgPxiIyJD1b4uiajBeOCBB264jSAIWL58eR1UQ0SBShRF6EosKDFZUYOR/ig2mLFodRqy80qcbYN6NMfdg9t6LZNIBAGhGgWDP9U7ter537JlC9asWYOxY8ciNTUVDz30EAYMGIDXX38dx48f91SNRORBziH/baL8/oM6TZACbZqHAQAOXF2ngIjqhiiKlf6x2+24cOECfv/9d+Tk5MDhcP/xW0RE5URRRJHBjBJjzYJ/od6Et1burxD8h/Ru4fXgHxaigFrJhYip/qn1x1WJiYlITEzEv/71L6SmpmL9+vX48ssvsWzZMsTHx2PUqFG444470KQJ5+sS1SVDqQWlJlul9j+O5wAAWsVocaWgtEbHFoSy5+fWha5to3DqfBEOpOdicE8+U5yorqxYsaLK13755Rf85z//wdNPP12HFRFRICkP/kaTDTXI/SgoNmHhqv3ILTI6227vF4c7bmrtxeAPaDUM/lR/eWysikQiwU033YSbbroJOp0Ozz77LDZv3owFCxZg4cKF6NWrF6ZMmYKbb77ZU6ckomqUmmw4ca4AVttfPXNmqx0Z2WUr4EokAg6fyavRsdVKGZo2CvZInTeS3K4xvtqWjoOnciGKot+PViBqCG655RbceeedeOWVV/D555/7uhwiqmccDhGFejPMlpoF/9wiIxau3I8C3V/rjt15U2vcntLKc0X+jUQAtMEKBPPRw1SPeXSiyh9//OF8JFBxcTHatm2L0aNHQyaT4ZtvvsFjjz2G6dOn48knn/TkaYmoClabo0L4P3dJB1EEQjUKqJWyCq+5Qy6ru6G+7ePCoVRIUag34/xlPVo21dbZuYmoai1atMAXX3zh6zKIqJ4pC/4mmCw1G0GYU1CKhav2o0hvdraNvaUNbuvd0lMlViIIQEiQAsFqhdfOQVQXah3+T58+jfXr1+OHH37ApUuXEBkZiTFjxmDUqFHo0KGDc7vJkyfjP//5D1auXMnwT+QjWVcMAIBmjf17ob9ryWVSdGodif0nriDtVC7DP5EfsNls2LRpE8LDw31dChHVI3aHiCKdCaYaTh3MzjPg7VVp0JVYnG333NoOg3o091SJlQgCEKJWQBPE4E/1X63C/6hRo3Dq1CkoFAoMHjwYzz33HG666SZIJNdfR7B379746quvanNKIqqFv8K/xseVuCepbRT2n7iCg+m5GD0w3tflEDUIVc3n1+v1OHDgAPLy8jBv3rw6roqI6iub3YEivRnmGgb/rCt6LFqdBn2p1dk2aWgCBiQ381SJlQgCoFEpEBLM4E+BoVbhX6vV4r///S+GDx8OjebGYWLw4MHYtm1bbU5JRDVUYrI658bFRtWz8N8uCgBw5EwerDYH5LJaPaiEiFywd+/eSm2CICA0NBTdu3fH3Xffjf79+/ugMiKqb6w2B4r0JlhqON3w3GUd3lmdhpKrCxkLAO6/vQP6JcZ4sMqKBAEIVsmh1TD4U+CoVfh//fXXERERAZVKdd3XTSYTCgoKEBNT9oOpVqsRGxtbm1MSUQ1dvNrr3yhMDbWyfj2XtmUTLcI0ShQZzDh5rgCd4xv5uiSigPfzzz/7ugQiCgAWqx2FejNs9poF/4yLxVi85gCM5qvBXwCmjOyE3p289yQxAUCQSo5QjdJr5yDyhVp1nw0ePBhbt26t8vWff/4ZgwcPrs0piMhD6uuQf6DsyQRd25b1/h84levjaoiIiMgVZosNBTpTjYN/+oVCLPoyzRn8JRIBD4/q7PXgr1bJEMqh/hSAatX9J4rVP5zDarVWOf+fiOqOKIq4cEUPAGheD8M/ACS1a4QdaVk4kJ6L+4Z3uPEOROSWffv21Wi/nj17ergSIgoERrMVxQYL7I6aPMwPOJFZgPe+OQiLteyDA5lUwCOjuzg7A7yhPPiHaZR8tDAFJLfDv8FggE6nc35dVFSE7OzsStvpdDps3LgRUVHe+wElItcUl1hgKLVCIgho2ijY1+XUSNe2jQEA6ecLYTBaoVHzObtEnnT//fe79ceuKIoQBAHHjx/3YlVEVB+VGC3QlVjhuEFHYVWOZuTj/bWHnI8klkklmD62i9en/amUDP4U2NwO/8uWLcO7774LoGzhn1deeQWvvPLKdbcVRRGzZ8+uVYFEVHvlQ/6bRAZBLpP6uJqaiQpXIzZKg4u5Bhw+nYe+XZr6uiSigPLZZ5/5ugQiCgD6EgsMRgtq2OGPQ6fz8OG6Q7DZyw4gl0kwY1xXtI+L8GCVlakUDP4U+NwO/ykpKQgKCoIoinjjjTcwYsQIdOrUqcI2giBArVajU6dO6NKli8eKJaKaycopG/LfrHGIjyupnaR2UbiYa8CBU1cY/ok8rFevXr4ugYjquWKDGSUmK2rY4Y+0k1fw8XdHnFMFlAopnhjXFW1bhHuwyspUCinCQ5SQSBj8KbC5Hf6Tk5ORnJwMADAajRgyZAgSEhI8XhgReYYoiriYW38X+7tWUrsobEg9i4PpXPSPiIjIX4iiiCKDGUazrcbB/4/jOfhk/VHnVAGVUopZ9ySjdWyoByutTCWXIixExeBPDUKtFvx74oknPFUHEXlJXpERJosdcpkEjSOCfF1OrXSJbwSJRMDF3BJcKSxF4/D6fT1E/s5sNmPLli04duwY9Ho9HI6KK3aXT/8joobL4SgL/iazDTXM/dhz+BKWbzzm/OAgSCXDrPHJiGuq9Vid16OUSxGmVUHK4E8NhFvhf8mSJRAEAY899hgkEgmWLFlyw30EQcCMGTNqXCAR1c6Fq/P9Y6M09f6XW7BajnbNw3DiXCEOnsrFkN4tfV0SUcC6ePEiHnjgAVy8eBFarRZ6vR6hoaHQ6/Ww2+0IDw9HUBA/gCNqyOwOEUV6E0wWe42P8dvBi/hi0wnnBwcatRxPTkhG82jvTVUUBAEqhQzhIcp6/7cRkTtqFP4feeQRKBQKhn+ieuDilcAY8l+ua7sonDhXiAMM/0ReNX/+fBgMBqxZswbNmjVDv379sHDhQnTv3h2fffYZvvjiCyxdutTXZRKRj9jtDhTqzTBbax78t/95Aau3nnJ+rQ1W4MkJyYiN8u7fLEFqJcI0CkilfCQ5NSxuhf8TJ05U+zUR+Reb3YHsvBIAgRP+k9s1xpdbT+Hg6Vw4HCLn6BF5yZ49ezBx4kQkJiaiqKjI2a5QKPDwww/jzJkzeOWVV/Dhhx/6rkgi8gmrzYEivQkWm+PGG1fhp9/P4+uf051fh2qUmDMxGU0ivftIYqVcCo1Kwr8fqEHix11EAexyfglsdgfUShkitCpfl+MR7VqEQ6WQothgQeYlna/LIQpYJpMJsbGxAACNRgNBEKDX652vJycn488///RVeUTkI1abHYW62gX/zbszKwT/cK0ST93bzevBXyGTIEyjhN1m9ep5iPyVx8O/0WjE119/jZUrV+LixYuePjwRueFCzl9D/gPlubVymQSd4xsBAA6c4qr/RN7StGlT5OTkAABkMhmio6Nx4MAB5+unT5+GUqn0UXVE5Atmqx0FOhOs9poFf1EU8f2vGfh2xxlnW6NQFZ6a1N3ri/jKpRKEhagglQbG30NENVGr1f7/9a9/4dChQ/jhhx8AABaLBffccw/S08s+yQsJCcHy5cvRsWPH2ldKRG47n1PWSxcoQ/7LJbWLwh/Hc3Dg1BWMvaWNr8shCkh9+vTBtm3bnE/2GTNmDD788EPodDo4HA6sX78eo0aN8nGVRFRXzBYbCvVm2B01W9NfFEV8u+MMtuw552xrHK7GnIndEO7l0YkyqYBwrRJymQRWi1dPReTXahX+9+7dizvvvNP59Q8//ID09HS8+eabaN++PWbOnIklS5bgvffeq3WhROQeo9mGy/nl8/29t2KuLyS1iwIAHD1bAIvVDoVc6uOKiALPo48+isOHD8NisUChUGD69Om4cuUKtmzZAolEgpEjR+Lpp5/2dZlEVAeMZiuKDZZaBf+vf07Htn0XnG1NIoMwZ2I3hGq8O4JIKhUQHqKCXMa/FYhqFf7z8vKc8wEB4KeffkLnzp0xcuRIAMA999zDlYCJfOTU+UKIYtnKudpgha/L8agW0SGI0CpRoDPjeGYBuraN8nVJRAEnJiYGMTExzq+VSiVefvllvPzyyz6siojqmsMhoshggaOGwd8hivhy60ns2P/XdODYKA2enJDs9b9PpJKy4M9OAqIytZrzr1arnYv/2Gw2/P777+jfv7/z9eDg4AqLAxFR3TmeWQAg8Ib8A2WPEC0P/AfTOe+fyBt27NgBu73mj/AiosAgOv/HfQ5RxBebT1QI/i2iQzBnUrc6Cv5KKBn8iZxqFf47deqENWvW4NixY3j//fdRUlKCQYMGOV8/f/48IiMja10kEbnvr/AfWEP+y5UP/U/jon9EXjFt2jT069cP//nPf7B79244HDVf2ZuIGh6HQ8RnG44h9WC2s61VjBazJyZDo5Z79dxSiYCwECWUiloNciYKOLX6iZg9ezYefvhh3HXXXRBFEUOHDkViYqLz9a1bt6Jbt261LpKI3FOoNyHryl8r/Qei8p7/M1lF0JdaEBIUWFMbiHzto48+wsaNG7FlyxZ8/fXXCA8Px9ChQzFixAj06NHD1+URkR+z2x349Idj+ON4jrOtTbNQzLg7CWqldwO5RBAQqlFAxeBPVEmtfiq6dOmCTZs2Yf/+/dBqtejVq5fzNZ1Oh0mTJlVoI6K6cSg9DwAQFab2+i9ZX4kMVaN5dAgu5OhxKD0PKV1jbrwTEbnspptuwk033QSr1YrffvsNGzduxPfff4/Vq1cjKioKQ4cOxe23347k5GRfl0pEfsRmd2Dpd0cqjMxLaBGOx8Ylej2QSwQBYSEKqJXeHVlAVF/V+icwIiICt956a6V2rVaLyZMn1/bwRFQD5fPgm0cH5pD/csntonAhR48D6bkM/0ReIpfLccstt+CWW26BxWLBzp07sWnTJnz99df44osvcOzYMV+XSER+wmqz48N1R3D4TJ6zrWOrCEwfm+j1RfckAqDVMPgTVccjH78ZDAZkZ2dDp9NBFCuvCNKzZ09PnIaIXCCKojP8t2gS2OG/a7sorP81AwdOXfF1KUQNQmlpKQoKCpCXlwez2Xzd3/lE1DBZrHa8v/YQjp0tcLZ1iY/Eo2O6eP0xexKh7OlGwSoGf6Lq1Cr8FxYW4sUXX8SPP/543RWBRVGEIAg4fvx4bU5DRG64nF+KK4VGSCUCYqOCfV2OV3VuHQmpRMDl/FJczi9Bk8jAvl4iX9Dr9fjxxx+xceNG7N27FzabDe3atcOsWbNw++23+7o8IvIDZosd7319ECfPFzrbktpF4eFRnSGT1mp98RsSBCAkWIFgNdf+IbqRWoX///znP/jll19w//33o0ePHtBqtZ6qi4hq6MDVXv/WsaGQy6Sw2gJ3he4glRwJLcNx7GwBDpzKxbC+DP9EnvLtt99i8+bNSE1NhdVqRevWrTF9+nQMHz4c8fHxvi6PiPyE0WzDu18dwOmsYmdbjw7ReHBkR0jrIvirFdAw+BO5pFbhPzU1FZMnT8Y///lPT9VDRLVUPgS+Y6sIH1dSN5LaNcaxswXYf/IKhvWN83U5RAFj3rx5aN68OaZOnYrhw4ejffv2vi6JiPxMqcmKxWsO4Gy2ztnWu1MTTB7RERKJ4NVzlwf/kGAGfyJX1Sr8q1QqxMbGeqoWIqolu0N0rvTfsVUkjGabjyvyvh4dGmPllhM4cOoKrDa71+cVEjUUX3/9NTp37uzrMojITxmMVryzOg3nc/TOtpSuMbh3aPs6Cf7BKjmDP5GbajUW584778RPP/3kqVqIqJbOZBXBYLQiWCVDq5iGMQ0nPjYMYSFKGM12HMsouPEOROQSBn8iqoquxIKFK/dXCP4Du8Xi3mF1F/xDNUqvnocoENWq53/o0KHYt28fHnroIYwfPx5NmjSBVFq5161Tp061OQ0RuSjt6pD/xLZRkEq8O8/OX0gkAnq0j8ZP+85j3/EcdG0X5euSiIiIAlaxwYyFq/bjcn6ps21wz+YYN6gtBMHLwR9l6/0w+BPVTK3C/6RJk5z/f9euXZVe52r/RHXrwKmyxf6SGlgA7tGhLPz/cfwyHh7F3koiIiJvKNSZsHDVflwpNDrbhvZpidED4+sk+KtVMoRyqD9RjdUq/L/66queqoOIaslktuFEZtmw94YW/pPaRUEqEXAxtwTZeQbENNL4uiQiIqKAkldkxNur9iOv2ORsG9m/FUaktKqz4B+mUXr9XESBrFbhf8yYMZ6qg4hq6UhGPmx2EY0jgtA0Mhi513wqH+iC1XJ0ah2JQ6fz8MfxHNx5E8M/ERGRp1wpKMVbq/ajQPdX8B89ML7OnrKjUjL4E3mCxyYFX7lyBSdOnEBpaemNN67GmTNn8OCDDyIpKQkpKSmYP38+LBaLS/vm5OTg//7v/9CnTx8kJiZi+PDhWL9+fa3qIaovyof8J7eLapC/HHt0iAYA/HEsx8eVEBERBY6sK3q8+cWfFYL/uEFt6y74Kxj8iTylVj3/APDTTz/hzTffxLlz5wAAn3zyCfr27YuCggJMnToVM2bMwJAhQ1w6VnFxMSZPnoy4uDgsXrwYOTk5eO2112AymfDss89Wu++VK1cwfvx4tGrVCi+++CI0Gg3S09Nd/uCAqL47cHWxv4Y25L9cjw7R+OT7ozh8Jh8msw0qZa3/80bUoHz77bc12m/06NEerYOI/Me5Szo88/4uFBnMzrYJQ9rh5u7N6+T8KoUU4SFKrz9BgKihqNVfxz///DNmzpyJpKQkjBw5EkuWLHG+FhERgejoaKxdu9bl8L969WqUlJRgyZIlCAsLAwDY7Xa88MILmDZtGqKjo6vc94033kCTJk3w8ccfO5840Ldv35pfHFE9UqAz4dxlPQQBSGzTMMN/s8YaREcEIaegFAfTc9G7c1Nfl0RUr8ybN8/tfQRBYPgnClA2uwMvfbrXGfwFAJOGtcdNSbF1cn6VXIrwEBWDP5EH1Sr8v/vuu+jRowdWrFiBwsLCCuEfAJKSkvDll1+6fLydO3eib9++zuAPAMOHD8dzzz2H1NRUjB079rr7GQwGbNq0Ca+88sp1HzVIFOjKh/zHNwuDtoGugisIAnp2iMYPqWex73gOwz+Rm7Zt2+brEojIj9gdIq4UlE3nFQRg8u0d0adL3fxuVcmlCNMy+BN5Wq3Cf3p6erU9BY0aNUJ+fr7Lx8vIyMBdd91VoU2r1SIqKgoZGRlV7nf06FFYrVbIZDLcd999SEtLQ1hYGEaPHo3Zs2dDLpe7XANRfVQ+5D+5gQ75L9ejY1n4//N4jvNRo0TkmtjYuunNI6L6QSmX4h/39sCvBy+iZ4dodGwdWWfnDdOqIGXwJ/K4WoV/tVoNo7HqFcUvXLhQoRf/RnQ6HbRabaX20NBQFBcXV7lfXl4eAOCZZ57BPffcgyeeeAKHDh3CO++8A4lEgqeeesrlGq4limKtFzB0V/n9rO6+BoqGdK2A965XFEVn+G/fQuv8nrVarbBaLLDYHB49HwDIJQ447I5qj2+1Wiv822UOCaxWa41+9uKbBkEhlyCv2IQTZ6+gZZMQt49RUw3p+7khXSvgX9fLD7WIqC7dlByLfl1jcKWgFA5R9Pr5lPKyOf4M/kTeUavw37t3b3z77beYPHlypddyc3OxZs0a3HLLLbU5hUscjrLw0a9fP+dIhD59+qCkpASffPIJZsyYAZVK5fZxrVYrjh8/7tFaXZWZmemT8/pCQ7pWwPPXm1NkRaHeArlUgFh6GceP50AqlUJQhCDnSg5MFptHzwcAoRoVGocrcSU3F0Zz9Ytq5uXnuXVslUKGpuECci/pYbfb3a4trrECpy6asOnXYxjYufKHid7WkL6fG9K1Av5zvQpF3U3tyc3Nxddff41jx45Br9c7f9+WEwQBy5cvr7N6iChwKWSSsuAv9djDyIjob2oV/mfPno3x48dj3LhxGDZsGARBwG+//YY9e/bgyy+/hCiKmDFjhsvH02q10Ov1ldqLi4sRGhpa7X5AWeC/Vt++ffH+++/j3LlzSEhIcLmOcnK5HG3atHF7v9owGo3IzMxEXFwc1Gp1nZ67rjWkawW8d73pv2UCyEGn1hHo0rmjs71Qb0V0Y9ErPf/BKhmC1EFoHBVVbc9/Xn4eGkU2cmvqjUImQaPIRggPqdm8wkGlF3Hq4jGcvSJieocONTpGTTSk7+eGdK2Af13v6dOn6+xcJ06cwAMPPACTyYRWrVrh1KlTaNOmDXQ6HXJyctCiRQs0adKkzuohosClkEkQrlUx+BN5Wa3Cf+vWrbFy5Uq8/PLLWLRoEURRxNKlSwEAvXr1wnPPPYdmzZq5dby/z+3X6/XIzc1F69atq9zvRgHdbDZX+3pVBEFAUFBQjfatLbVa7bNz17WGdK2A56/30OlCAEDvzjEVjmswlUKuUAASLwz7V8ggkUpcOr5cLnerp1Iuk0Aul9f4HvVPboEP1x9H5mU9dEYRTSKDa3ScmmpI388N6VoB/7jeuhzyv2DBAgQFBeHbb7+FSqVCv3798K9//Qt9+/bFpk2b8Pzzz+PNN9+ss3qIKDCVB38Zgz+R19X6p6xt27ZYtmwZ9uzZgzVr1uDLL7/Erl278NlnnyE+Pt6tYw0YMAC7du2CTqdztm3evBkSiQQpKSlV7hcbG4t27dph165dFdp37doFlUpV5733RHWlxGjFsbNli2r26FD1ozAbklCNEp2vLkq069AlH1dDVH/t378f48ePR0xMDCSSsj8XxKtzfocPH4477rgD8+fP92WJRFTPKWQShIUw+BPVlRr3/FssFnz33XdITU3F+fPnUVJSguDgYLRs2RI33XQTRo4c6fa8xAkTJmDFihWYMWMGpk2bhpycHMyfPx8TJkxAdPRfwWby5MnIzs7G1q1bnW1z5szB448/jpdffhk333wzDh8+jE8++QQPPfSQz3tqiLzlQHou7A4RsVGaOu/h9mf9EmNw6HQedh3Oxthb+OEfUU04HA40atQIQNn0OqlUiqKiIufrCQkJ+Oabb3xUHRHVd3JpWfCXyxj8iepKjX7aTp48ieHDh+PZZ5/F5s2bceHCBZhMJly4cAGbNm3Cv//9b4wcORJnzpxx67ihoaFYvnw5pFIpZsyYgQULFmDcuHGVHifocDgqLQQ2aNAgvPXWW9i9ezemTZuGNWvWYObMmZg9e3ZNLpGoXvjzeA4A9vr/Xd8uTSEIwMlzhcgv9v0K7UT1UbNmzZCVlQUAkEgkaNasGXbv3u18ff/+/QgJqbsnahBR4JBLJQjXKhn8ieqY2z3/JSUleOyxx1BQUIA5c+Zg1KhRFXrlc3Jy8O233+J///sfpk+fju+++86tnvf4+HgsW7as2m1WrFhx3fbbb78dt99+u8vnIqrPRFHEnyfKw39jH1fjXyK0KrRvGYHjmQXYffgSRvaves0QIrq+/v37Y/PmzZgzZw4AYOLEiXjttddw4cIFiKKI33//HQ8++KCPqySi+kbmDP5SX5dC1OC4/XHb2rVrcenSJXzwwQd49NFHKwR/AIiOjsa0adPwv//9D1lZWVi3bp3HiiWiv5zN1qFAZ4ZKIUWnq3Pc6S/9EsueFsB5/0Q1M336dCxYsABWqxVA2ZS7WbNmoaioCHq9Ho8//jhH1xGRW2RSAeEhDP5EvuJ2z//27duRkpKC3r17V7td37590a9fP/z888+49957a1wgEV3fH1eH/HdtG8VfotfRp3NTLF1/FEcz8lBsMCNUo/R1SUT1SmhoaIXH7AqCgMcffxyPP/64D6siovpKKhUQHqKCQs6/WYh8xe2e/1OnTqFXr14ubdunTx+cOnXK7aKI6MbKw393zve/riaRwYhvFgqHCOw5ctnX5RDVOw888ECFOf5/t2fPHjzwwAN1WBER1VcM/kT+we3wX1xcjKioKJe2bdSoEYqLi90uioiqpy+14OS5AgBA9/ac71+Vfl1iAAC7Dmf7uBKi+uf3339HXl5ela8XFBRg3759dVgREdVHUomAcI0SSgZ/Ip9zO/xbLBbIZK7NFpBKpc65gkTkOWknr8AhAi2bhKBxOB9lWZW+Xcrm/R9Kz4XByP8WEblLEIQqXzt37hyCg/mIUSKqmlRSNsdfqajx08WJyINq9JN48eJFHD169IbblT8iiIg86w8+4s8lzaND0Dw6BBdy9NhzOBu39mrp65KI/Nq6desqLNT7v//9D2vWrKm0nV6vx8mTJzFgwIC6LI+I6hEGfyL/U6OfxkWLFmHRokU33E4UxWp7DYjIfQ6HiD9PXAHA+f6uGNgtFp9vOoFf/sxi+Ce6AaPRiMLCQufXJSUlkEgqDxIMCgrChAkTMGPGjLosj4jqCalEQBiDP5Hfcfsn8tVXX/VGHUTkolPnC6ErsSBIJUOHuAhfl+P3bu7WHJ9vOoHDZ/KQW2hEVLja1yUR+a1JkyZh0qRJAIBBgwbh3//+NwYPHuzjqoioPpFIBIRqFFAx+BP5Hbd/KseMGeONOojIRbsOlz23vmeHJpBJ3V62o8GJjghCp9aROJqRjx1pWRg3qK2vSyKqF37++Wdfl0BE9YxEEBCmUUCtlPu6FCK6Dn4kR1SPiKKI3VdXru+b2NTH1dQft3RvjqMZ+fjlzwu465Y2nI5E5Ibff/8d27dvR3Z22X97YmJicPPNN7v82F8iahgkgoCwEAZ/In/G8E9Uj2Re0uFyfikUMgm6J/ARf65K6RqDD9YdwvnLemRcLEZ8szBfl0Tk9ywWC5566in89NNPEEURWq0WAKDT6fDpp59iyJAhWLBgAeRy/qFP1NBJhLKh/gz+RP6NY4aJ6pFdh8qG/Hdr3xgqJT+7c5VGLUevjk0AAL/8yaeQELni3XffxdatW/Hggw/it99+w++//47ff/8dqampmDp1Kn788Ue8++67vi6TiHxMIgBajQJBKgZ/In/H8E9UjziH/HfhkH933dK9GQBgZ1oW7HaHj6sh8n/ff/89xowZg3/+859o1KiRsz0yMhL/7//9P4wePRrr16+v0bHPnDmDBx98EElJSUhJScH8+fNhsVjcOsayZcuQkJCAadOm1agGIqo9iQCEBCsQzOBPVC8w/BPVE9m5Bpy7rIdUIqDn1V5scl239tEICVKgUG/GwfQ8r5xDKpV65bhEvpCbm4vExMQqX09MTERubq7bxy0uLsbkyZNhtVqxePFizJkzB2vWrMFrr73mVm3vvvsuIiMj3T4/EXmGIAAhQQpo1Apfl0JELuK4YaJ6YvfVVf67tGmEkCD+onWXXCbBgORYbEg9ix/3nkOzxhqPHt9qtUJQhMBkdSDIo0cm8o0mTZrg999/x8SJE6/7+r59+9CkifsfRK5evRolJSVYsmQJwsLCAAB2ux0vvPACpk2bhujo6Bse44033sCgQYOcixASUd0SBCBErYCGf48Q1SsM/0T1RHn478ch/zV2S/dm2JB6FvuOX0aPDo09uuq/1WJBYVE+GkU2AkI9dlginxk9ejQWL16MkJAQTJkyBS1btoQgCMjMzMTy5cuxefNmzJw50+3j7ty5E3379nUGfwAYPnw4nnvuOaSmpmLs2LHV7v/HH3/gp59+wubNm/HUU0+5fX4iqh1BADQqBUKCGfyJ6huGf6J6IK/IiJPnCyEIQO/ODP811a5FOGKjNLiYa8DhM/noEBfhsWNbbA5YLDaPHY/I16ZPn44LFy5gzZo1+OqrryCRlM0UdDgcEEURY8aMwfTp090+bkZGBu66664KbVqtFlFRUcjIyKh2X7vdjhdffBHTp09H48aee+KJ0Wj02LEauvJ7yXvqGf5wP0URMJmMsDtECIIAjVoOmcSG0tL6+TvPH+5pIOH99DxRFL32WGqGf6J6YM+Rsl7/9i0jEKFV+bia+ksQBAzrG4el64/g0Ok8tG8Z7rX/uBLVd1KpFK+99hqmTJmCnTt34uLFiwCA2NhYDBgwAO3bt6/RcXU6nfOxgdcKDQ1FcXFxtfuuXLkSRqMRU6ZMqdG5q5KZmenR4xHvqaf58n7KZDIUGGyw2+0ICVLBIBeRZaufwf9a/B71LN5Pz1IovDOyhuGfqB4oH/LPVf5rb3DP5li+4RjyiozIKShFk8hgX5dE5Jeys7MRERGB9u3bXzfom0wmFBQUICYmpk7qyc/PxzvvvIPXX3/d438UxcXFQa1We/SYDZXRaERmZibvqYf4w/0URSC3yAiVQgptAAz194d7Gkh4Pz0vPT3da8dm+Cfyc4V6E45k5ANg+PeEkCAFenWMxq7Dl3A0I5/hn6gKgwcPxvz583HHHXdc9/Wff/4ZTz31FI4fP+7WcbVaLfR6faX24uJihIZWvWDGokWLkJCQgB49ekCn0wEAbDYbbDYbdDodgoKCIJPV7M8atVqNoCAu1elJvKee5cv7aXeI0NolCA9RBtRoOX6Pehbvp+d48+eM4Z/Iz6UezIbDIaJdizAGVQ8Z2K0Zdh2+hPQLRUjpGgOVgv8pJPo7URSrfd1qtTrXAXBH69atK83t1+v1yM3NRevWravc7+zZs9i3bx969uxZ6bWePXvio48+woABA9yuh4iqJxGAME1gBX+ihop/8RL5uR37swAAA5Ob+biSwBEfG4pGYSrkFZlw8lwhuraN8nVJRH7BYDA4e9UBoKio6LqP09PpdNi4cSOiotz/2RkwYADef//9CnP/N2/eDIlEgpSUlCr3+9e//lWhNgB45ZVXoFKpMHfuXCQkJLhdCxHdmCAIYO4nCgwM/0R+7HJ+CU6cK4REAPonxfq6nIAhCAK6xDfCL39m4WhGPhLbNGKPBhGAZcuW4d133wVQ9nPyyiuv4JVXXrnutqIoYvbs2W6fY8KECVixYgVmzJiBadOmIScnB/Pnz8eECRMQHR3t3G7y5MnIzs7G1q1bAQAdOnSodCytVougoCD07t3b7TqIiIgaGoZ/Ij+2M61sde3ENlFc5d/D2sdF4NcD2SjUm5GdW4LYxhpfl0TkcykpKQgKCoIoinjjjTcwYsQIdOrUqcI2giBArVajU6dO6NKli9vnCA0NxfLly/Hiiy9ixowZCA4Oxrhx4zBnzpwK2zkcDtjt9lpdDxEREf2F4Z/IT4miiB1pV4f8d2Ovv6cp5VK0axGGY2cLcCQjn+GfCEBycjKSk5MBlK3gfNttt6Fdu3YeP098fDyWLVtW7TYrVqy44XFc2YaIiIjKuL9SDxHVidNZRTh/WQ+FTII+XermUVoNTefWkQCAjItFMBitPq6GyL888cQTXgn+RERE5BsM/0R+atu+CwCAPl2aQqOW+7iawBQVHoSmkcFwiMDh03m+LoeIiIiIyGsY/on8kMVqd67yP7hnCx9XE9iS2pWtVn40Ix8WG+cXExEREVFgYvgn8kO/H7sMg9GKRqEqPobOy+JitAjVKGC22nEis9DX5RAREREReQXDP1EdkkqlLm330+/nAQC39GgOqYSPoPMmiSA4P2A5mJ4Lhyj6uCIiIiIiIs/jav9E1TCUWlBqsnnkWFarFYIiBIV6KwymUgSpZNAEKSptd6WgFPtPXgEA3Moh/3Wifctw7D16GboSC85mFyM+NszXJREREREReRTDP1E1Sk02nDhXAKvNUetjWS0W5FzJQXRjEUFBKrRvGXHd8L9l7zmIItC1bSPERPHxc3VBLpOic+tI/HniCg6eymX4JyIiIqKAw/BPdANWm8Mj4d9ic8BkscFic0BexfFsdgd+3HsOADC8b6tan5Nc1yW+EdJO5eJSfiku55egSWSwr0siIiIiIvIYzvkn8iN7jlxCkd6M8BAlendu4utyGpRgtRztmocBAA6k5/q2GCIiIiIiD2P4J/Ijm3ZlAgBu690SMil/POta+WP/zmQVo1Bv8nE1RERERESew3RB5CfOZhfj0Ok8SCQChvaJ83U5DVJkqBpxTbUAgP0nrvi4GiIiIiIiz2H4J/IT63dmAABSEmMQFa72cTUNV48O0QCAU+cLoSux+LgaIiIiIiLPYPgn8gNFejO2788CANw5oLWPq2nYoiOC0LyxBg4RSDvJ3n8iIiIiCgwM/0R+YNOus7DZHUhoEY72LSN8XU6DV977fyyzACVGq4+rISIiIiKqPYZ/Ih8zmW34/rezAIBRA+J9XA0BQEyUBk0jg+FwiEg7xZX/iYiIiKj+Y/gn8rEf956DvtSCppHB6JfY1Nfl0FU9OjQGABzNyIfRbPNxNUREREREtcPwT+RDVpsD67afBgCMvaUNpHy8n99oHh2CqHA1bHYHDqaz95+IiIiI6jcmDSIf2v7nBeQVmxChVWJwz+a+LoeuIQgCerQvm/t/+HQezBa7jysiIiIiIqo5hn8iH7HZHViz7RQAYPTANpDLpD6uiP6uVYwWEVoVLDYHDp/J83U5REREREQ1xvBP5COph7JxOb8UYSFKDO8X5+ty6DoEQUD39mVz/w+m58JiY+8/EREREdVPDP9EPmCzO/DD1RX+xw1qC5VC5uOKqCptmochVKOAyWLH0Yx8X5dDRERERFQjDP9EPnA0Ix8FOhMitCoM7xvn63KoGhJBQLeEst7/tJO5sNkdPq6IiIiIiMh9DP9EdcxitWPPkcsAgHtubQeFnHP9/V1CywiEBMlhNNvY+09ERERE9RLDP1Ed+//t3XlclWX+P/7XWdkPyA5uCAjigrgiYWSWGdlkGiqahdHHmIZyUmfKmn5+aWxxaJpKrFHLxmVKs9R2LbMSxSXNfUcWUZFdOIf1bPfvD5KJUITDOdxneT0fDx7FzX1fvK7rPnjO+16u+0hu83Pjg3zcMHFMX7HjUAfIpBKM+HXm/yPnynj2n4iIiIhsDot/om5U32TAyfwqAMC0u/pDLuOfoK0Y0LcH3F0UqGvU42xhldhxiIiIiIg6hZUHUTc6c6kRRqOAPgEeiA73FTsOdYJMJm259/+Xs2UwGHn2n4iIiIhsB4t/om5SUlmPq1U6AMDtw3pCIpGInIg6K6qfN1yd5aht0OFs4TWx4xARERERdRiLf6JuIAgC9p8qBQBE9vGCn5eLyInIFPI2Z/8FkRMREREREXUMi3+ibnC+6BrKqxshkwIjB/iJHYe6YGA/H7g4yaGp1+J8Ec/+ExEREZFtYPFPZGGNWj1yjl8FAPQPdoars1zkRNQVCrkUwyKbD+AcOlMKI8/+ExEREZENYPFPZGH7TlxFQ5MeXu5KhAY6iR2HzGBwqA+clTKo67TIvcSz/0RERERk/Vj8E1nQ1Yo6nC5ofizc2KFBkEo5yZ89UMhlGBbRfO//obNlMAo8+09ERERE1o3FP5GFGIwCfjp8GQAwIKQHgnxcRU5E5jQ4zAdOShmqNU3Iu1wtdhwiIiIionZZXfGfl5eHxx57DDExMYiPj0dmZia0Wm2n2lizZg0iIyORlpZmoZREt3YstxxV6kY4K2W4bUiw2HHIzJQKGWL6N9/7f/BMKQSe/SciIiIiK2ZVxX9NTQ1SUlKg0+mQlZWF+fPnY9OmTVi6dGmH2ygvL8c777wDHx8fCyYlap+6TouDp0sAALdFB8PFiZP82aMh4b5QKqS4pm5CwVWN2HGIiIiIiG7KqiqSjRs3oq6uDsuXL4eXlxcAwGAw4KWXXkJaWhoCAgJu2cbrr7+O8ePHo7i42MJpiW5MEARkH7kMvUFAsK8bBvTtIXYkshAnhQxDw/1w8EwpjpyvwJ1D3MWORERERER0Q1Z15j87OxtxcXEthT8AJCYmwmg0Iicn55bbHzp0CN9//z0WLlxowZRE7cu/UoOLJRpIJRKMG94LEgkn+bNn0f19oZBLUaVuQnFV525RIiIiIiLqLlZV/Ofn5yM0NLTVMpVKBT8/P+Tn57e7rcFgwJIlS/DHP/4R/v7+loxJdFNanQG7j14BAAyP9EMPlbPIicjSnJVyRIf7AgDOFNXz3n8iIiIiskpWddm/Wq2GSqVqs9zT0xM1NTXtbvvRRx+hoaEBc+bMMVseQRBQX19vtvY6oqGhodV/7Zkt9FWn00Gn1UKrN3Zo/b0nSlDXqIfKVYEhYT1aTVap0+l+06YUOp3Ooq+vzmbvDIXUCKPB2G77v+1vpxhtb2wG9vXEsdxyVNcZcCy3HN4qpVnatVa28LdrTtbUX0EQeDURERERmcSqin9TVVZWYtmyZfjHP/4BpdJ8H7p1Oh3OnDljtvY6o7CwUJTfKwZr7atMJoNE6YHSslI0avW3XL+6To9TBbUAgKjeSpSXl95wvYrKCtQq5QjqIUH5VQ0MBoNZcwOdz95Znu7O8O/hhLLycjQ0tX+pe0VlRafadrbRsenrr0Te1SZ8lVOAYPdaGI3mP+hibaz1b9dSrKW/5nyfIyIiIsdhVcW/SqWCRtN2xuyamhp4enredLu3334bkZGRGDlyJNRqNQBAr9dDr9dDrVbD1dUVcnnnu6pQKBAeHt7p7bqioaEBhYWFCAkJgYuLS7f+7u5mC329ptEhwF+45RlioyBg/+5CAEBYTxWiI3u2WUen06GisgK+Pr5wc3GCr48vengEWSI2gI5nN4WbsxyuLq7w9/Nr98z/9f4qFIoOt62US21ybNzcG1BYWojL5Q1okPogJtLXbG1bG1v42zUna+rvhQsXRP39REREZLusqvgPDQ1tc2+/RqNBeXl5m7kAfqugoAAHDx7EqFGj2vxs1KhReO+995CQkNDpPBKJBK6urp3ezhxcXFxE+93dzZr7WttYD4VSCUjbLxKPX6hARXUjlAopbh/WC0rlzYtdhUIBhVIJhUJh0X53NLspFEo5pDJph9pXKBSdOlOpkEttcmxU7kBooDNyixuxdVch4qJ72/3l2db8t2sJ1tBfe39NERERkeVYVfGfkJCAFStWtLr3f/v27ZBKpYiPj7/pdi+88ELLGf/rXn31VTg7O2PBggWIjIy0aG5ybHUNOuw/eRUAMGZwENycO36Wm+xLRC9XFJZpcfbiNRzPrcDQCD+xIxERERERAbCy4j85ORnr169Heno60tLSUFpaiszMTCQnJyMgIKBlvZSUFBQXF2PHjh0AgKioqDZtqVQquLq6IjY2ttvyk2Pac+wKdHoj/Hu4YlCoj9hxSEQuSinGDg3Cj79cwYYd51j8ExEREZHVsKpH/Xl6emLt2rWQyWRIT0/HG2+8gaSkJCxatKjVekaj0SITgRF11sUSNS5croEEwLjhPSHlJbkO757RfSCXSXEqvxIn8jo32SERERERkaVY1Zl/AAgLC8OaNWvaXWf9+vW3bKcj6xB1hd5gRPaRKwCA6P6+8OvhOPc+08318HDChNg+2La3EJu+P48hYfY78R8RERER2Q6rOvNPZEsOnSmFuk4LdxcFRg8MFDsOWZGH7uwPmVSCo+fLce5ildhxiIiIiIhY/BOZolrThCPnygEAt8f0hFIhEzkRWZMAb1fcOaI3AODj78+LnIaIiIiIiMU/kUlyjhfDKAjoE+CBfsEqseOQFUq6qz+kEuDg6VLkXa4WOw4REREROTgW/0SdVFSiQeFVNaQSIH5oMJ+7TTfU088dY2N6AgA+2ZkrchoiIiIicnQs/ok6wWAUsOd48yR/Q8J84a1yFjkRWbPpd0UAAPaeKEZRiVrkNERERETkyFj8E3XCqfwKXFM3wVkpw8iBAWLHISvXN0iFuCFBEATgkx949p+IiIiIxMPin0Qlk9nORHmNTXr8fKoUABA7KBDOyq49KZM3C9ycPY3N9bP/2Ycv42pFnchpiIiIiMhRda16IeqA2not6hv1bZbrdDpIlB64ptGhtrHepLZdneVwd1V2NWKH/Hy6BE06A3w8nTGwn0+X2pJJJdAbjSirMq3ftyKRAFqdwSJtW5q9jU14by+MGOCPX86W4dMfcvH09Jhu+91ERERERNex+CeLq2/U4+zFKuj0xlbLdVotSstKEeAvQKHsfAGvkEsxoK93txT/1bVNOJVfCQAYOzQYUmnXzk1LpRI0ag24VFrdZlzMwcVJjiBfN7O32x3scWxm3B2JX86W4YdDRZgxIQL+PVy79fcTEREREbH4p26h0xvbFHJavRGNWj20eiMgNX+RZ04/nyqBUQD6BHqgl7+H2dq90biYg0Ju3ePZEfY0NlH9vBEd7ovjFyqw5ccL+OPU6G7PQERERESOjff8E91CeXUDci9VAwDGDAoUNwzZrBkTmu/9/+7ARVSpG0VOQ0RERESOhsU/0S3sO14MAAjv5Qk/Xq5NJhoS5ouoEG/o9EZs/emC2HGIiIiIyMGw+Cdqx4XL1cgvVkMiAWIHBYkdh2yYRCLB9Lubz/5v21eImtomkRMRERERkSNh8U90E4IgYMuPzWdoB/T1hpeHk8iJyNaNGOCPsF6eaNIa8MXufLHjEBEREZEDYfFPdBNHzpfjXNE1yKQSjBoYIHYcsgMSiQQzfj37/9WefNQ26ERORERERESOgsU/0Q0IgoD135wGAESH+8KjGx4nSI4hdlAQ+gR6oL5Rj6/38Ow/EREREXUPFv9EN7D3xFVcuFwDJ6WMZ/3JrKRSCabf1Xz2//PsPDQ06UVORERERESOgMU/0e8YDEb8d9sZAMA9o/vC1VkhciKyN2NjeiLY1w2aeh227S0QOw4REREROQAW/0S/8+Mvl3C5rBYergrcE9tH7Dhkh2RSCabd1R8AsPWnPDTpDCInIiIiIiJ7x+Kf6Dd0egM++u4cACBpfATP+pPFjBvRG/49XFBd24Tv9l8UOw4RERER2TkW/0S/sW1fIcqvNcBb5YxJY/uJHYfsmFwmRdL45rP/W37MhU7Ps/9EREREZDks/ol+1dCkxyff5wIAku+JhJNCJnIisnd3jeoDb5UzKmoa8cOhS2LHISIiIiI7xuKf6Fdf7M5DdW0TgnzcMGE07/Un00gkHV9XqZBh6p3hAIBNO3Oh0xstlIqIiIiIHJ1c7ABE1kBTr8XWHy8AAGbdOwByGY+LUefJZVIIggRlVfUd3mZ4pD9UbkqUVdVj608XMG54r3bXd3WWw91V2dWoRERERORgWPwTAdj8Qy7qGvUICVIhIaan2HHIRslkUjRqDcgrVnfqLP6wSD/sOnwFW3+6AE935U0PPinkUgzo683in4iIiIg6jcU/ObwqdSO+3NP8rPVH7ouCVNqJ67aJbkCnN3aq+B/Q1xu/nClDbYMOR8+XY2h/PwumIxJfXl4eXn75ZRw5cgRubm6YPHkynnnmGSiVNz+wVVZWhjVr1iAnJwdFRUXw8PDAqFGjsGDBAvTsyYO2REREt8Jrm8nhfbzjHLQ6Awb07YFRUQFixyEHJJdJMeLX194vZ8t47z/ZtZqaGqSkpECn0yErKwvz58/Hpk2bsHTp0na3O3XqFHbs2IHExES8++67WLRoEc6fP49p06ahqqqqm9ITERHZLp75J4dWUlmHb399xvqjkwZC0pnZ2ojMKCqkBw6fLYOmXouTeRUYFukvdiQii9i4cSPq6uqwfPlyeHl5AQAMBgNeeuklpKWlISDgxgdhR4wYgW3btkEu/99Hl+HDh2PcuHH47LPPkJqa2h3xiYiIbBbP/JND++jbszAYBQyP9MeQMF+x45ADk0mlGDWwueg5fK4MWp1B5ERElpGdnY24uLiWwh8AEhMTYTQakZOTc9PtVCpVq8IfAAIDA+Ht7Y2ysjJLxSUiIrIbLP7JYV0sUeOnw5cBAI8kRomchgiI7NMDnu5KNGoNOH6hQuw4RBaRn5+P0NDQVstUKhX8/PyQn5/fqbYKCgpQWVmJsLAwc0YkIiKyS7zsnxzWuq/PQBCA+OhghPf2EjsOEaRSCUYPDMSOn4tw+FwZBoX6wMWJ/0yTfVGr1VCpVG2We3p6oqampsPtCIKAl19+Gf7+/pg0aVKXMjU0NHRpe/qf62PJMTUPjqf5cUzNi+NpfoIgWOxWZH6qJId0Mq8CP58ugVQqwezEAWLHIWrRv7cXjp4vR3l1Aw6eKeWjJ4luIisrC/v378f7778PV1fXLrVVWFhonlDUgmNqXhxP8+OYmhfH07zae/pNV7D4J4cjCALWfHUaADAxti96+XuInIjofyQSCW6LDsLn2fk4lVeB6HBfeLk7iR2LyGxUKhU0Gk2b5TU1NfD09OxQG5s2bcI777yDV155BXFxcV3OFBISAhcXly63Q81n/woLCzmmZsLxND+OqXlxPM0vNzfXYm2z+CeHs/f4VZwrugZnpQwz74kUOw5RG738PdAn0ANFJRrsP3kV944JETsSkdmEhoa2ubdfo9GgvLy8zVwAN7Jjxw5kZGRg3rx5SEpKMksmFxeXLl89QK1xTM2L42l+HFPz4niajyWfPsYJ/8ih6A1GrPum+az/g3eEo4fKWeRERDd225AgAEDe5RqUVNaJnIbIfBISErB3716o1eqWZdu3b4dUKkV8fHy72x44cAALFizAtGnTkJ6ebumoREREdoXFPzmUb/dfRHFFHTzdlZgyjrNDk/Xy8XTBgJAeAJqvVhEEQeREROaRnJwMNzc3pKenY8+ePdi8eTMyMzORnJyMgICAlvVSUlIwYcKElu/z8vKQnp6OkJAQTJ48GUePHm35KioqEqMrRERENoWX/ZPDqG/UYeN35wAAyRMi4eqsEDkRUftiBwbiwqVqXK2sQ0GxGpF9e4gdiajLPD09sXbtWixZsgTp6elwc3NDUlIS5s+f32o9o9EIg8HQ8v2xY8eg0Wig0Wgwc+bMVutOmTIFS5cu7Zb8REREtorFPzmMTd+fR3VtE4J83DCR91CTDXB3VWJofz/8crYMOceLEdazY5OhEVm7sLAwrFmzpt111q9f3+r7qVOnYurUqRZMRUREZN942T85hEulGnyenQcAePyBQVDI+dIn2zB8gD/cXRRQ12lx6Gyp2HFayGQysSMQERERUSfwzD/ZPUEQsGrrCegNAkZGBWD0oECxIxF1mFIuw23RwfjuwEUcPF2KBxPC4O9tudl0a+u1qG/Ut7uOTqeDROmBaxodahvrO9y2q7Mc7q6WeW4tEREREbWPxT/ZvZzjxTiaWw6FXIonHhxi0cdnEFlCeC9PnC5wx+WyWmzYcQ4vh/la7HfVN+px9mIVdHrjTdfRabUoLStFgL8AhbJjxbxCLsWAvt4s/omIiIhEwmufya41NOnx/ucnAQBJ4/sjyNdN5EREnSeRSHB7TE9IJcCx3Ar8fLrEor9Ppze2+6XVG9Go1UN7i/V+/0VERERE4mHxT3bt4x3nUFnTiABvVzw0vr/YcYhM5q1yxrBIfwDAe5+dgFZnuMUWRERERET/w+Kf7NbFq+qWSf6eeHAInBScoIxsW+ygQPTwcEJJZT027jgndhwiIiIisiEs/sku6Q1GvLnxMPQGAbGDAjnJH9kFpUKGWfcMAABs/iEX54uuiZyIiIiIiGwFi3+yS5/+kIu8yzVwd1HgT0lDxY5DZDbDB/gjYVhPGAXgrY2Hefk/EREREXUIi3+yO7mXrmHjd82XRKdNjYa3ylnkRETmlTYlGl4eTrhUWouPvj0rdhwiIiIisgEs/smu1DXokLn+EAxGAbdFB+GOYT3FjkRkdio3JdJ/vaJl608XcPZilciJiIiIiMjasfgnuyEIAt759BhKKuvh38MFT08fBolEInYsIosYMzgI40b0ar78f8MRNGr1YkciIiIiIivG4p/sxtaf8rD76BXIpBL89ZGRcHdRiB2JyKKeeHAIvFVOuFJei1VbT4gdh4iIiIisGIt/sguHzpRizdenAACPPzAYA/p6i5yIyPI8XJVYMHMEpBJgx89F2HHgotiRiIiIiMhKsfgnm3fhcjUy1x+CIAATx/TF/WP7iR2JqNsMjfDDrHubH/+3Ystx5F+pETkREREREVkjFv9k00oq65Dx3j40NOkxJMwXaVOieZ8/OZxp4yMwMioAWr0RS9ceRG2DTuxIRERERGRlWPyTzarWNOGNjw6jplaL0J6eeDF1NBRyvqTJ8UilEiyYNRz+PVxwtbIOb288DKNREDsWEREREVkRVkpkk6rUjfhk53lUqRvR088dL82Ng6szJ/gjx+XhqsSilFGQy6TYf7IE/91+RuxIRERERGRF5GIHIOqsK+W12LavEE1aA3r6uWPhrOHQ6gwoq6o36++RSACtzmDWNoksqX/vHnhq2lC8tfEIPtmZiyAfN0yI7St2LCIiIiKyAiz+yaacLqjErsNXYBQEBPm44qlpQ3G1sg5FpRqz/y4XJzmCfN3M3i6RJd01qg+uVtTh4+/PY/mnx+DuqkDckGCxYxERERGRyHjZP9kEvcGIHw5dwo+/XIZREBDWyxMzJkTCzUUBnd5okS+9wSh2t4lM8vC9AzB+ZG8YjQIy1x/CoTOlYkciIiIiIpFZXfGfl5eHxx57DDExMYiPj0dmZia0Wm2725SVlSEzMxOTJ0/GsGHDkJCQgIULF+LKlSvdlJosqbSqHpu+P48zhVUAgNEDAzExti8n9yO6CYlEgnnTYzB2aDD0BgGvrvkZR8+XiR2LiIiIiERkVdVTTU0NUlJSoNPpkJWVhfnz52PTpk1YunRpu9udOnUKO3bsQGJiIt59910sWrQI58+fx7Rp01BVVdVN6cnc9AYj9p0oxuYfcnFN0wQXJzkeuD0UowYG8HF+RLcgk0mx8OERiB0UCJ3eiCUf/IwTeRVixyIiIiIikVjVPf8bN25EXV0dli9fDi8vLwCAwWDASy+9hLS0NAQEBNxwuxEjRmDbtm2Qy//XneHDh2PcuHH47LPPkJqa2h3xyYxKq+qx82ARrmmaAAARfbxwe0xPOCut6iVLZNXkMimee3QkXvnPz/jlbBky3tuPZ2ePQOzgILGjEREREVE3s6oz/9nZ2YiLi2sp/AEgMTERRqMROTk5N91OpVK1KvwBIDAwEN7e3igr46WutuRGZ/sTbwvBhNF9WfgTmUAhl+H5OaMxMioAWp0Br675Gdv2Fogdi4iIiIi6mVUV//n5+QgNDW21TKVSwc/PD/n5+Z1qq6CgAJWVlQgLCzNnRLKg6/f2Hz5XDgHNZ/tnTYxEaLCn2NGIbJqTQoYXHxuNCaP7wCgA724+jnXfnIYgCGJHIyIiIqJuYlWnUtVqNVQqVZvlnp6eqKmp6XA7giDg5Zdfhr+/PyZNmmRyHkEQUF9v3mfH30pDQ0Or/9oDnU4HnVYLrd7YZjkANGm1OHyuHIfPVUAA4OIkw9joIIQEeQAw3nTCR4XUCKPBeMO2zcHc7V/v7/XxsKXsprT/2/6au+2usFT71/tpNFouO4xS6HQ6k/9devz+CHi6yfHpj/n4ZGcurpSpkfbgIDgrZS3r3Ozv9bdM2rddzC4ma/p3WRAEznlCREREJrGq4t9csrKysH//frz//vtwdXU1uR2dToczZ86YMVnHFRYWivJ7zU0mk0Gi9EBpWSkatfo2P2/UGvF1zkVUapp/FuyjwOC+LlBKanG1pLbdtj3dneHfwwll5eVoaGr/iRCmsFT7FZUV0DXZZnZT2q+o7Nwkc9aU3ZS2G5saLZbdWSlHUA8Jyq9qYDAYTGpjcBCgje2BL3++hr0nSnGhqBLTb/eBr0pxy7/X3+vMvjVHdrFZy7/LSqVS7AhERERkg6yq+FepVNBoNG2W19TUwNOzY5d+b9q0Ce+88w5eeeUVxMXFdSmPQqFAeHh4l9rorIaGBhQWFiIkJAQuLi7d+rst5ZpGhwB/oc2ZxILiamSfLIFWL0Auk2BsdBD69+74Jf5uznK4urjC38/PImdZzd2+TqdDRWUFfH184eXhYlPZTWn/t/1VKBRmbbsrLNW+TqeDrqkWzk7OFsuulEvh6+OLHh5dm7AvKgoYNvga3v74OMpqtFi9oxJ/mjoIoyP8b/r3+lum7FtzZReDNf27fOHCBVF/PxEREdkuqyr+Q0ND29zbr9FoUF5e3mYugBvZsWMHMjIyMG/ePCQlJXU5j0Qi6dKVA13h4uIi2u82t9rGeiiUSkDaXEwIgoDD58qw/2QJAMBH5YR74/rBy8OpU+0qlHJIZdJWbZuTpdpXKBRQKJU2md2U9hUKRafOVFpT9s7SNQFSqQWzy6VQKBRm+bdh5EBXvL3QB/9YdxCnC6rwxoZjePCOMCTGhXQ4f2f2rTmzi8Ua/l3mJf9ERERkKqua8C8hIQF79+6FWq1uWbZ9+3ZIpVLEx8e3u+2BAwewYMECTJs2Denp6ZaOSiYyGgX8dPhyS+Hf11+JB24P6XThT0Rd561yxitPxmNyQvPEqJ/tysNraw+i+tdHbBIRERGR/bCq4j85ORlubm5IT0/Hnj17sHnzZmRmZiI5ORkBAQEt66WkpGDChAkt3+fl5SE9PR0hISGYPHkyjh492vJVVFQkRlfoBgxGI747cBGnC6ogARA3OABDQlwhl1nVy5DIochlUvzf5MF4Yc5ouLsoUHhVjQ+/PYtzRdfEjkZEREREZmRVl/17enpi7dq1WLJkCdLT0+Hm5oakpCTMnz+/1XpGo7HVhFHHjh2DRqOBRqPBzJkzW607ZcoULF26tFvy083pDUZs33cRhVfVkEolmBjbF738XHC15KrY0YgIQNyQIIT38sJra39G7qVqfP9zES6XanD7sJ5QymW3boCIiIiIrJpVFf8AEBYWhjVr1rS7zvr161t9P3XqVEydOtWCqagrjEYB3+5vLvxlUgnuuy0EfQJVN32EHxHdnCXv+Pbr4YK/zh6BD748hQMnS3D24jWUVNbjntg+8Othu/fqExEREZEVFv9kXwRBwH+3n0HupWpIJRJMiu+H3gEeYsciskkyqQR6oxFlVfUWaV8iAQwGAWMGByHIxw3f/VyE6tomfPrjBdw2JAjR4b6ccI6IiIjIRrH4J4va8uMF7DpyBRIJMCG2Dwt/oi6QSiVo1BpwqbQaOgs8StDFSY4gXzcAQLCfO5LvjsAPv1xCQbEae44V41KpBneN6gMZ638iIiIim8Pinyxm/8mrWPvNaQDAHcN6IbyXl7iBiOyETm+0SPGvkLdu09lJjsS4EJzMq0TO8WJcLNHg4x3ncNfIXmb/3URERERkWZxmnSziUqkG//roFwgCcOeIXoiJ8BM7EhGZQCKRYEi4L5LG90cPDyfUNerx9d6LuFzBOTuIiIiIbAmLfzK7xiY9lq47iIYmA4aE+WLmPZFiRyKiLvL1ckHS+P7oF6yCwSjgaH49DpwqhVEQxI5GRERERB3A4p/M7t9bjqOoRIMeHk746+wRkEn5MiOyB0qFDIlxIYjp7wMAOJ5XhW9yCqDTG26xJRERERGJjVUZmVXOsWL8cOgSpBLgr4+MRA+Vs9iRiMiMJBIJRkX5Y3iYK2RSCS6WaPDF7nw0aXkAgIiIiMiasfgns7mmacS7m48BAJLuisCQMF+RExGRpQT7KHF/fF84KWQoqazH1l0XUN+oEzsWEREREd0Ei38yC0EQ8O6nx6Cu0yIkSIXkCbzPn8je+fdwwYN3hMHFSY7KmkZs/SkPmnpOBEhERERkjVj8k1n8+Mtl7D9ZArlMggWzhkMh50uLyBH4erlg6p3h8HBVoLq2CVt/usADAERERERWiBUadVlFdQNWbT0OAEi+JxL9gj1FTkRE3cnL3QlTxoXDy90Jmnodvtidj4YmvdixiIiIiOg3WPxTlwiCgHc+PYa6Rj369/ZC0p39xY5ERCLwcFXigYRQuLsoUK1pwpe786HVcRJAIiIiImvB4p+65ODpUhw6Uwq5TIL5M4dDJuNLishRXT8A4KyUoby6AV/nFEBvMIodi4iIiIjA4p+6QKsz4L3PTwAAJieEoXeAh8iJiEhsPTyc8cDtoVDKpSiuqMO3+y/CKAhixyIiIiJyeCz+yWSf7cpDSWU9vFXOmMHZ/YnoV349XDEpvh9kUgkKr6qx/8RVsSMREREROTwW/2SS8msN2LTzPADgsfsHwsVJLnIiIrImwX7uGD+yNwDgyPlynC6oFDkRERERkWNj8U8m+c9Xp9CkNWBgP2/cMbyX2HGIyApF9OmBEQP8AQA7D17ChcvV4gYiIiIicmAs/qnTTuRVYPfRK5BKgLQp0ZBIJGJHIiIrFTsoEKHBnjAYm58MUlZVL3YkIiIiIofE4p86xWAwYtXW5kn+Jo4JQWhPT5ETEZE1k0gkuHt0b/h5uUBdp8Ura37mIwCJiIiIRMDinzpl+75CFF5Vw91FgdmJUWLHISIboJDL8MDtoXB3VSD/Sg3e+/yk2JGIiIiIHA6Lf+qwmtom/Hf7WQDA7MQoqNyUIiciIlvh4abE3MlDIJE0H0T84dAlsSMRERERORQW/9Rh67edQW2DDv2CVbg3LkTsOERkYwaH+iD518eCvrv5GC6WqEVOREREROQ4WPxTh1y4XI3vDlwE0DzJn0zKSf6IqPNmTIhETIQfmrQGvLbmIOobdWJHIiIiInIILP7plgRBwKqtJyAIQMKwnhgU6iN2JCKyUTKpBH95eAR8PJ1xpbwW7356HIIgiB2LiIiIyO6x+Kdb+unwZZwprIKzUobUPwwSOw4R2ThPdyc8+8hISKUS7DpyGd//XCR2JCIiIiK7x+Kf2lXfqMOar04BAKbfHQEfTxeRExGRPRjYzwez7x0AAFix9QSKeP8/ERERkUWx+Kd2fbzjPKrUTQjydcODd4SJHYeI7MhDd/ZHTIQftDoD/rH+EBq1erEjEREREdktFv90U5fLNPhidx4AYO7kwVDIZSInIiJ7IpVKsGDWcPTwcEJRiQbvf35S7EhEREREdovFP92QIAh47/OT0BsEjIwKwKiBgWJHIiI71MPDGQtnjYBEAny7/yKyj1wWOxIRERGRXWLxTzd08HQpDp8tg1wmxdzJg8WOQ0R2bGiEH6bdFQEAWP7JMRRX1IqciIiIiMj+sPinNrQ6A977/AQA4ME7whDs5y5yIiKyd7PuicTAft5oaNLj9fWHoNMbxI5EREREZFdY/FMbW3+6gJLKenirnDH97gix4xCRA5DJpPjr7JHwcFXgwuUarPn6tNiRiIiIiOwKi39qpaSyDpu+Pw8ASP3DILg4yUVORESOwtfLBc8kDwcAfJGdjwMnr4qciIiIiMh+sPinFoIgYOXWE9DqjRja3xcJw3qKHYmIHMzoQYGYnND8WNG3Pz6C8msNIiciIiIisg8s/qnF/pMlOHSmFHKZBH+cGg2JRCJ2JCJyQCmTBiK8txc09Tq8/t9DMBiMYkciIiIisnks/gkA0Nikx6rPmif5m3pnf/Ty9xA5ERE5KoVcimdnj4SLkxxnCqvw0XfnxI5EREREZPNY/BMAYOOOc6ioboC/tyum3dVf7DhE5OCCfN3w9LQYAMAnO8/j6PkycQMRERER2TgW/4SLV9X4bFceACBtyhA4KznJHxGJ7/ZhPTFxTF8IAvDGR4dxTdModiQiIiIim8Xi38HpDUa8ufEwDEYBYwYHYvTAQLEjERG1mPvgEPQN9EC1pgn/+vAwjEZB7EhERERENonFv4P79Idc5F2ugYerAn96aKjYcYiIWnFSyPDsIyOhVMhwNLccn/6QK3YkMoO8vDw89thjiImJQXx8PDIzM6HVam+5nSAIWLVqFcaNG4fo6GjMmDEDR48etXxgIiIiO8Di34HlX6nBxl8n0kqbEo0eKmeRExERtdUnUIU/ThkCAPjw27M4XVApciLqipqaGqSkpECn0yErKwvz58/Hpk2bsHTp0ltu+95772HZsmWYM2cOVq5cCT8/P6SmpuLSpUvdkJyIiMi2sfh3UDq9EW9uaL7cP25IEBKG9RQ7EhHRTd09ug/GDe8Fo1HA6+sPoVrTJHYkMtHGjRtRV1eH5cuX4/bbb0dSUhL++te/YuPGjSgtLb3pdk1NTVi5ciVSU1MxZ84cxMXF4V//+he8vLywevXqbuwBERGRbWLx76A+/v4cCq+qoXJT4k8PDYVEIhE7EhHRTUkkEjz5UDR6+rmhoqYRr/znALQ6g9ixyATZ2dmIi4uDl5dXy7LExEQYjUbk5OTcdLvDhw+jtrYWiYmJLcuUSiUmTJiA7OxsS0YmIiKyC5zW3QGdKajCJzub75t98qFoeHk4iZyIiOjWXJ0VeDE1Fn9ZthtnL17D2x8fwV8eHsGDlzYmPz8fDz30UKtlKpUKfn5+yM/Pb3c7AAgNDW21PCwsDGvXrkVjYyOcnTt3+5pOpwMA5Obm8nVkJoLQPCknx9Q8OJ7mxzE1L46n+el0OouNJYt/B6Ou0yJz/UEYjQIShvXE2KG83J+IbEcvfw88nzIK/2/VPmQfuYJe/h6YeU+k2LGoE9RqNVQqVZvlnp6eqKmpaXc7pVIJJ6fWB6xVKhUEQUBNTU2ni//rH66kUl4IaS4SiQRKpVLsGHaD42l+HFPz4nian0QiYfFPXWc0Cnhr42FU1DQi2NcN6Umc3Z+IbM/Q/n548qGhWP7JUXz07Vn09HNDwrBeYsciGzRs2DCxIxAREXUbHup2IBt3nMPB06VQyKV47tFRcHVWiB2JiMgkE8f0xYN3hAEA3txwBIfPlomciDpKpVJBo9G0WV5TUwNPT892t9NqtWhqaj3Zo1qthkQiaXdbIiIiYvHvMPYeL8aGXx/rl540FKE9+SGJiGzbnPsHIT46GHqDEa/85wBOXKgQOxJ1QGhoaJt7+zUaDcrLy9vcz//77QCgoKCg1fL8/HwEBwd3+pJ/IiIiR8Pi3wGcL7qGf204DAB44PZQ3DWqj8iJiIi6TiaVYOHDIzB6YCC0eiP+vno/zhRUiR2LbiEhIQF79+6FWq1uWbZ9+3ZIpVLEx8ffdLvhw4fD3d0d27Zta1mm0+nw3XffISEhwaKZiYiI7AGLfztXXFGLv6/ejyatAcMi/JD6h0FiRyIiMpvm25hGIibCD41aAzLe34fzRdfEjkXtSE5OhpubG9LT07Fnzx5s3rwZmZmZSE5ORkBAQMt6KSkpmDBhQsv3Tk5OSEtLwwcffIC1a9di3759WLhwIaqrq/H444+L0RUiIiKbwuLfjpVfa8DilftQU6tFeC9PLEoZBZmMu5yI7ItSIcPfHhuNwWE+qG/U4/9buRcn8ngLgLXy9PTE2rVrIZPJkJ6ejjfeeANJSUlYtGhRq/WMRiMMBkOrZXPnzsVTTz2FDz74AE888QRKSkqwevVq9O7duzu7QEREZJM427+dKr/WgBf+vQelVfUI8nHD4v8bwwn+iMhuOSvl+P9SY/H31QdwKr8S/2/VPvzl4RG4LTpY7Gh0A2FhYVizZk2766xfv77NMolEgrS0NKSlpVkoGRERkf3iaWA7dLlMg0Xv7kFJZXPh/+qf4tHDgxMhEZF9c3VW4O9PxCF2UCB0eiNeW3sQn+w8D0EQxI5GREREJDoW/3bmbGEVns3ag7KqegT5uuGVJ+Ph6+Uidiwiom6hVMjwfMooTIrvBwBY980ZvP7fX1DfqBM5GREREZG4WPzbkW/3F+L5d3Ogqdeif28vZD51O/x6sPAnIscik0nxx6nRePKhaMikEuw+egXPvLkLuZc4ESARERE5Lhb/dqCuQYc3NxzG8k+OQW8wYszgQLzyZDy8PJzEjkZEJJr7buuHpelj4evlgqsVdfjLst1Yv+0MdHrDrTcmIiIisjMs/m3c4bNlePqNH/HDoUuQSIBHEqPwfMpouDhxLkciogEh3li2cBxuj+kJo1HApu/PI/31H3HwdInY0YiIiIi6FStEG1VcXov/fHUK+082f4AN9HHFM8nDMSjUR+RkRETWxcNViWcfGYn46GCs3HocVyvq8PfVBxAd7ouH7x2Agf347yYRERHZP6s785+Xl4fHHnsMMTExiI+PR2ZmJrRa7S23EwQBq1atwrhx4xAdHY0ZM2bg6NGjlg/czS6VavDWxsN4MvMH7D9ZAqlUggcSQrFs4Z0s/ImI2hE/NBgrFt2FqePCIZdJcfxCBZ5bvgeL3tmDfSeuQm8wih2RzIifJ8zPlDEtKytDZmYmJk+ejGHDhiEhIQELFy7ElStXuim19TL1Nfpba9asQWRkJB9/+auujGlpaSmee+45jBkzBtHR0UhMTMQXX3xh4cTWzdTxvHbtGhYvXoxx48YhJiYG999/PzZs2NANia3fxYsXsXjxYkyePBkDBw7E/fff36HtzPXeZFVn/mtqapCSkoKQkBBkZWWhtLQUS5cuRWNjIxYvXtzutu+99x6WLVuGv/zlL4iMjMSHH36I1NRUfP755+jdu3c39cAyGrV6HDhZgu9/LsLR3PKW5SOjAjBn0kD0DVKJmI6IyHa4Oivw2B8GYdLYfvh4x3nsPFiEU/mVOJVfCZWbEmOHBmPc8N4YENIDEolE7LhkIn6eMD9Tx/TUqVPYsWMHHnroIQwdOhTXrl3Dv//9b0ybNg1fffUVvL29u7EX1qMrr9HrysvL8c4778DHhyd/gK6NaVlZGWbMmIF+/fphyZIlcHd3R25ubqcPxtiTroznn//8Z+Tn52PBggUICgpCdnY2MjIyIJPJMH369G7qgXXKzc3Frl27MHToUBiNxg4/jthc701WVfxv3LgRdXV1WL58Oby8vAAABoMBL730EtLS0hAQEHDD7ZqamrBy5UqkpqZizpw5AIARI0bg3nvvxerVq5GRkdE9HTAToyDgSnkdCkrKcehMKY6cK0OjtnmCKqkEGDUwENPu6o/Ivo75hklE1FX+PVzx9PQYzJoYiS9352PnwUuorm3CN3sL8c3eQvh6uWBof19Eh/siPNhN7LjUSfw8YX6mjumIESOwbds2yOX/+8g5fPhwjBs3Dp999hlSU1O7I77VMXU8f+v111/H+PHjUVxcbOG0tqErY/r6668jMDAQ77//PmQyGQAgLi6uO2JbLVPHs7y8HAcOHMBrr72GqVOnAmgeyxMnTuDrr792+OJ//PjxuPvuuwEAixYtwsmTJ2+5jTnfm6zqsv/s7GzExcW1vMAAIDExEUajETk5OTfd7vDhw6itrUViYmLLMqVSiQkTJiA7O9uSkbtMU6/FuYtV+PGXS/jv9jN4bd1hZG4uxoJle5G16Sj2nbiKRq0BAd6umHF3BFY+fzdeTI1l4U9EZAY+ni6Yc/8grFl8DzLmjsGdI3rBxUmGiuoG7Dx4CW9uOIL0N/bgX59dxWvrDmPNV6fww6FLOHexCpU1DTAYO3bEnrqXI36esDRTx1SlUrUq/AEgMDAQ3t7eKCsrs1Rcq2fqeF536NAhfP/991i4cKEFU9oWU8e0trYW27Ztw6xZs1oKfzJ9PPV6PQDAw8Oj1XJ3d/cOn+W2Z1Jp58tvc743WdWZ//z8fDz00EOtlqlUKvj5+SE/P7/d7QAgNDS01fKwsDCsXbsWjY2NcHZ2Nn/gDioorsFPv1xGdW0T1HVaqOuaUFPb/N+Gphs/ckohlyKiTw8MDffFyIEBCO/lxUtQiYgsRCaTYsSAAIwYEIBGrR6n86tw/EI5TuZVIvdyNdT1BhzNrcTR3MrW20kl8PF0hsrdCe4uCri5KOD+65ebiwLOSjlUbkqMGRIEJwU/VHYXe/08ISZTx/RGCgoKUFlZibCwMHNGtCldGU+DwYAlS5bgj3/8I/z9/S0Z06aYOqanTp2CTqeDXC7H7NmzceTIEXh5eeHBBx/EM888A4VCYenoVsnU8QwKCsLYsWOxYsUK9OvXD4GBgcjOzkZOTg7++c9/Wjq2XTLne5NVFf9qtRoqVdv71z09PVFTU9PudkqlEk5OrZ9rr1KpIAgCampqOv1mrdPpIAgCjh8/3qntbqRa04TeKiN6qwBAAsD5169mUokEMpkEMqkEcpkEEghwUsp/PTKkRcO1Szhx7VKXc4jFaBTgITEC8tZH+wQ54BfiCqm0FqYc1pAYJagurbxh2+Zg7vZ/21+psc6mspvSvqn71xqym0KQA4KLHDUVRTaXvbPtm7RvJRIUF11DyWXbOIgpBzC8DzC8jxeMRhUatXoAEhiMgN5ghMEowHjDs/5GAE2/fjV/q9MAR46UwdW562+5Op2OB4I7wJo+T9gLU8f09wRBwMsvvwx/f39MmjTJnBFtSlfG86OPPkJDQ0PL5b/UzNQxraioAAC8+OKLmD59Op566ikcP34cy5Ytg1QqddirK7ryGs3KysL8+fNb/sZlMhlefPFFTJw40SJZ7Z0535usqvi3Jtc/XJnjQ1YPlWN+ULhOJpPARXazS1y6fjRVLrfs3Svmbb91f20ruyntm75/xc9uOoUNZ+94+45zJkQmk8HNxTrO2kskEhb/ZNOysrKwf/9+vP/++3B1dRU7js2prKzEsmXL8I9//ANKpVLsOHbBaGx+0sttt92GRYsWAQDGjBmDuro6fPDBB0hPT3fYg36mEAQBzz//PAoLC/HGG2/Az88Pe/fuxauvvgpPT0+HPuhnDayq+FepVNBoNG2W19TUwNPTs93ttFotmpqaWh0RUavVkEgk7W57M8OGDev0NkRERCQ+a/o8YS9MHdPf2rRpE9555x288sorDj+Zmqnj+fbbbyMyMhIjR46EWq0G0HyPtV6vh1qthqura5s5FhxFV/7ugeaC/7fi4uKwYsUKXLx4EZGRkeYNawNMHc+ffvoJ27dvxxdffNEybrGxsaisrMTSpUtZ/JvAnO9NVjXhX2hoaJt7SDQaDcrLy9vc4/D77YDme8h+Kz8/H8HBwTxaR0RE5ED4ecL8TB3T63bs2IGMjAzMmzcPSUlJloppM0wdz4KCAhw8eBCjRo1q+Tp8+DD27NmDUaNGYe/evZaObrVMHdPw8PB2221qajJLPltj6nheuHABMpkMERERrZZHRUWhrKwMDQ0NFslrz8z53mRVxX9CQgL27t3bciQTALZv3w6pVIr4+Pibbjd8+HC4u7tj27ZtLct0Oh2+++47JCQkWDQzERERWRd+njA/U8cUAA4cOIAFCxZg2rRpSE9Pt3RUm2DqeL7wwgtYt25dq68BAwYgJiYG69atQ3R0dHfEt0qmjmnPnj0RERHR5sDJ3r174ezsfMuDA/aqK+NpMBhw7ty5VstPnToFHx8fuLi4WCyzvTLne5NVXReUnJyM9evXIz09HWlpaSgtLUVmZiaSk5NbPUsyJSUFxcXF2LFjBwDAyckJaWlpyMrKgre3NyIiIrBhwwZUV1fj8ccfF6s7REREJAJ+njA/U8c0Ly8P6enpCAkJweTJk3H06NGWdb29vdGnT5/u7opVMHU8o6Ki2rSlUqng6uqK2NjYbstvjUwdUwCYP38+/vSnP+GVV17BuHHjcOLECXzwwQd4/PHHHXZuClPHMyEhAcHBwZg3bx7S09Ph7++PPXv2YOvWrXj66afF6o7VaGhowK5duwAAV65cQW1tLbZv3w4AGD16NLy9vS363mRVxb+npyfWrl2LJUuWID09HW5ubkhKSsL8+fNbrWc0GmEwtH5E3ty5cyEIAj744ANUVVUhKioKq1evRu/evbuzC0RERCQyfp4wP1PH9NixY9BoNNBoNJg5c2ardadMmYKlS5d2S35r05XXKN1YV8Z0/Pjx+Ne//oV3330XGzZsgL+/P55++mk88cQT3dkFq2LqeLq7u2PNmjV488038c9//hMajQa9evXCokWLMHv27O7uhtWprKzEn//851bLrn+/bt06xMbGWvS9SSIIgvmfF0VEREREREREVsOq7vknIiIiIiIiIvNj8U9ERERERERk51j8ExEREREREdk5Fv9EREREREREdo7FPxEREREREZGdY/FPREREREREZOdY/BMRERERERHZORb/IsvJycHChQtx9913IzIyEn//+987tN3ly5cRGRnZ5mv69OkWTmw6U/sKABqNBi+88AJGjx6NYcOGYd68eSgrK7NgWvP44Ycf8MADD2DIkCGYOHEiNm/efMttbGHf5uXl4bHHHkNMTAzi4+ORmZkJrVZ7y+0EQcCqVaswbtw4REdHY8aMGTh69KjlA3eRqf0dP378DfdlU1NTN6Q2zcWLF7F48WJMnjwZAwcOxP3339+h7Wx135raX1vct0Rkf65/ZtiyZYuoObZs2YLIyEhcvnxZ1BwdceDAAURGRuLAgQNiRyHqdnKxAzi63bt34+zZsxg1ahRqamo6vf2CBQsQGxvb8r2bm5s545lVV/r6zDPP4MKFC8jIyICTkxPeeustzJ07F5s3b4Zcbp0v40OHDuGpp55CUlISXnjhBezfvx9/+9vf4ObmhnvvvfeW21vrvq2pqUFKSgpCQkKQlZWF0tJSLF26FI2NjVi8eHG727733ntYtmwZ/vKXvyAyMhIffvghUlNT8fnnn6N3797d1IPO6Up/AWDixIlITU1ttUypVFoqbpfl5uZi165dGDp0KIxGIwRB6NB2trhvAdP7C9jeviUi27NlyxY8//zzN/zZ3LlzkZyc3Gb5rl27cPz4cTz99NOtljc0NOD999/H6NGjW32+6E43y9YZK1asQHh4OO6++24zJiNyDNZZNTmQZ599FosWLQIAk45A9u3bFzExMWZOZRmm9vXIkSPYs2cPVq9ejbFjxwIA+vXrh/vuuw/fffcd7rvvPovk7ap///vfiI6ObrnCYcyYMbh06RKWLVvWoeLfWvftxo0bUVdXh+XLl8PLywsAYDAY8NJLLyEtLQ0BAQE33K6pqQkrV65Eamoq5syZAwAYMWIE7r33XqxevRoZGRnd04FOMrW/1/n6+lrlfryZ8ePHt3ygWrRoEU6ePHnLbWx13wKm9fc6W9u3RGS75s2bh169erVaFhERgZ49e+L48eOtToTs2rULH3744Q2L/+XLl+Opp54Stfi/UbbOWLlyJSZOnMjin8gEvOxfZFKp4+wCU/uanZ0NlUqF+Pj4lmWhoaGIiopCdna2ueKZlVarxYEDB9oU+ffddx/y8vJs4rK4m8nOzkZcXFxLIQwAiYmJMBqNyMnJuel2hw8fRm1tLRITE1uWKZVKTJgwwWr3I2B6f22VKX+ntrpvAcf6N5iIbFdCQgImT57c6isqKgoSiQROTk6QyWRiRyQiG8BPPTYuIyMDUVFRiIuLw4svvojq6mqxI5ldfn4++vXrB4lE0mp5aGgo8vPzRUrVvqKiIuh0OoSGhrZaHhYWBgAdym2t+zY/P79Nv1QqFfz8/Nrt1/Wf3WhMiouL0djYaP6wZmBqf6/78ssvMXjwYAwbNgxz587FuXPnLBVVNLa6b7vKEfYtEVm339/zv2jRInz44YcA0Go+ksuXLyMuLg4AsHz58pblWVlZLW3l5eVh3rx5GD16NIYMGYKpU6di586dbX5nbm4uHn30UURHRyMhIQHvvvsujEbjLbPeLNt19fX1WLp0Ke644w4MHjwYEydOxOrVq1vdjhUZGYn6+nps3bq1ZfvrV5VeuXIFGRkZmDhxIqKjoxEbG4t58+bZ9AkXInPjZf82SqlUYubMmRg7dixUKhWOHTuGFStW4OTJk/jkk0+gUCjEjmg2arUaHh4ebZZ7enp26hLd7nR9TgOVStVq+fXv25vzwNr3rVqtbtMvoHl/tNcvtVoNpVIJJyenVstVKhUEQUBNTQ2cnZ3NnrerTO0v0HxJeXR0NIKDg3Hp0iWsWLECs2bNwmeffWbV98F3lq3u265wlH1LRNahtrYWVVVVrZZ5e3u3WW/GjBkoKytDTk4OMjMzW62bkZGBjIwMTJgwARMmTACAluI7NzcXM2fOREBAAObOnQtXV1ds27YN6enpyMrKalm/vLwcjz76KAwGA5544gm4uLhg06ZNbf79v5GbZQOaJ4198sknceDAASQlJSEqKgq7d+9GZmYmSktL8cILLwAAMjMz8eKLLyI6OrplIuQ+ffoAAE6cOIEjR45g0qRJCAwMxJUrV7BhwwY8+uij+Prrr+Hi4tKhsSayZyz+zUyj0XRoFvrevXt3aWIof3//VvfRjh49Gv3790daWhp27NjRLffBd1dfrUVn+tsV1rBvyTxefPHFlv8fOXIk4uPjkZiYaPX3wdOtcd8SUXe6Pp/Kb93oaqNhw4YhJCQEOTk5mDx5cqufTZw4ERkZGYiMjGzzs1deeQVBQUHYvHlzy2e2WbNmYebMmfjnP//ZUvy/9957qKqqwieffILo6GgAwJQpU3DPPffcsg/tZdu5cyf279+PZ555Bk8++SQA4OGHH8a8efOwbt06zJ49G3369MHkyZORkZGB3r17t2lj3LhxbW63vPPOOzFjxgx8++23ePDBB2+Zkcjesfg3s+3bt7f6UHgz33zzTcsl4OZyxx13wNXVFadOneqWArG7+qpSqVBSUtJmeU1NDTw9PU1ut7M609/ruTQaTaufqdVqAOh07u7et+1RqVRt+gXcen+oVCpotVo0NTW1OkOgVqshkUi6dV92hqn9vRF/f3+MGDECp06dMlc8q2Cr+9ac7HXfEpF1WLx4Mfr162eRtqurq7F//37MmzcPtbW1rX42duzYlifdBAQEYNeuXYiJiWkp/IHmqwr+8Ic/4KOPPjI5Q3Z2NmQyGR555JFWy1NTU/Htt98iOzsbs2fPbreN315hptPpUFtbiz59+kClUuH06dMs/onA4t/spk2bhmnTpokdo1t0V19DQ0Oxb98+CILQ6r7/goICREREWPz3X9eZ/mq1WigUCuTn5+P2229vWX6ze6NtyY3mWtBoNCgvL2+3X9d/VlBQgAEDBrQsz8/PR3BwsNVeFm5qfx2Jre5bIiJbER0djSFDhlik7aKiIgiCgLfffhtvv/32DdeprKxEQEAAiouLMXTo0DY/7+qBiStXrsDf3x/u7u6tll8/eXTlypVbttHY2IiVK1diy5YtKC0tbTVXwI0O4hM5Ihb/duTHH39EfX29xd4cxHJ9Mpl9+/bhtttuA9BcZJw+fRr/93//J3K6G1MqlYiNjcW3336LlJSUluXXr4L4/eN6bsWa9m1CQgJWrFjR6l747du3QyqVtnoiw+8NHz4c7u7u2LZtW0uBqNPp8N133yEhIaFbspvC1P7eSGlpKX755Zc2lyraOlvdt+Zkr/uWiOzf9cn6UlNTW52w+K3r99VbsyVLlmDLli1ISUlBTEwMPDw8IJFIMH/+/FYHAogcGYt/kV25cgUnTpwA0Pz81aKiImzfvh0AWt23NHDgQDz44IN49dVXAQBLly6FRCJBTEwMVCoVjh8/jpUrV2Lw4MFW+9xTU/s6bNgwjB07Fi+88AKee+45ODk54c0330RkZGSH7jETy5NPPolHH30UGRkZSExMxIEDB/DVV1/hzTffbLWere3b5ORkrF+/Hunp6UhLS0NpaSkyMzORnJzc6pn3KSkpKC4uxo4dOwAATk5OSEtLQ1ZWFry9vREREYENGzaguroajz/+uFjduSVT+/vVV1/hxx9/xB133AF/f39cunQJq1atgkwmw2OPPSZWd26poaEBu3btAtD8N1tbW9vydzp69Gh4e3vbzb4FTOuvre5bInIMv3860q2WX5+rSKFQtJxkuZng4GBcvHixzfKCgoIuZevZsyf27duH2traVmf/r19517Nnz1u2ff2+/uuz/wNAU1MTz/oT/QaLf5EdOHAAzz//fMv3u3fvxu7duwG0nsjFYDC0eoxKWFgYNmzYgE2bNqGxsREBAQFISkrCvHnzIJdb5241ta8A8NZbb+G1117D4sWLodfrMXbsWLz44otW21egeRKwrKwsvPXWW/j0008RHByMl19+udWz0AHb27eenp5Yu3YtlixZgvT0dLi5uSEpKQnz589vtZ7RaITBYGi1bO7cuRAEAR988AGqqqoQFRWF1atXW/Xs6Kb2t1evXigrK8Orr74KjUYDDw8PjBkzBvPmzbPq/lZWVuLPf/5zq2XXv1+3bh1iY2PtZt8CpvXXVvctETmG67Pa//5pNb9d/ls+Pj4YPXo0Pv74Y8yePRv+/v6tfl5VVdXyZIE77rgDa9euxfHjx1vu+6+qqsKXX37ZpWwJCQn4+OOP8eGHHyItLa1l+Zo1ayCRSFpdRebq6tqmDwAgk8naLFu/fn2b9ysiRyYReB0MEREREZHV2bJlC55//nl8+umnN7z17/Lly7jrrrvw2muvYerUqQCAbdu24ZlnnsHkyZMxduxYyGQyTJo0CQAwadIk1NTU4Mknn4SXlxf69++PiIgIXLhwAbNmzYJEIsH06dPRu3dvVFRU4OjRoygpKcEXX3wBACgrK8Mf/vAHCIKARx99tNWj/s6dO4edO3e2e2vjzbIZjUbMmTMHP//8M6ZPn47IyEjk5ORg586dSElJaXnUHwA88cQTOHjwIObNmwd/f3/06tULQ4cOxXPPPYcvv/wSDz/8MMLDw3H06FHs3bsXjY2NuPPOO7F06VIAzSejHn300ZYDvESORPzTiEREREREZBb33HMPHnnkEXz99df44osvIAhCS/H/8ssvY8mSJXjttdeg0+nw1FNPISIiAuHh4di8eTOWL1+OrVu3orq6Gt7e3hg4cCDS09Nb2vb398e6devw8ssvY9WqVfDy8kJycjL8/f3xt7/9zeRsUqkU//73v7Fs2TJ888032LJlC3r27Ilnn30WqamprdpYtGgRFi9ejLfeeguNjY2YMmUKhg4dir/97W+QSqX48ssv0dTUhOHDh+M///mP1c4PRSQGnvknIiIiIiIisnNSsQMQERERERERkWWx+CciIiIiIiKycyz+iYiIiIiIiOwci38iIiIiIiIiO8fin4iIiIiIiMjOsfgnIiIiIiIisnMs/omIiIiIiIjsHIt/IiIiIiIiIjvH4p+IiIiIiIjIzrH4JyIiIiIiIrJzLP6JiIiIiIiI7ByLfyIiIiIiIiI7x+KfiIiIiIiIyM79/xXrdPeOghKmAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e6b449f429bd4f729fc27095e4ae4a6a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.07437069 -0.39371621  0.17096942 -0.04284533]\n",
            " [-0.03362678 -0.43370508 -0.08941246  0.04461255]\n",
            " [-0.04787596 -0.33227533 -0.07807848 -0.05926594]\n",
            " [-0.01971611  0.20235889  0.27468544  0.13022538]\n",
            " [-0.07334744 -0.45928997  0.13270464 -0.07625173]\n",
            " [-0.02891998  0.10731886 -0.1331558  -0.13316874]\n",
            " [ 0.0494146  -0.30157609 -0.09024128 -0.04486102]\n",
            " [ 0.02682724  0.14929487 -0.1329292   0.11715953]\n",
            " [ 0.01721661  0.18973495  0.26363171  0.12036601]\n",
            " [-0.02881137  0.15244752 -0.14058135  0.11726814]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb9873dd70>\n",
            "Shape values [0.07437069 0.13022538 0.20235889 0.27468544]\n",
            "Shap values final [-0.00644685 -0.11194076  0.01775926  0.01732388]\n",
            "Coefficients: \n",
            " [[ 0.00221591 -0.31127841  0.11752841 -0.08309659]]\n",
            "Mean squared error: 0.01\n",
            "Coefficient of determination: 0.89\n",
            "Evaluating classroom: Class 1 - STI\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb99162ef0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.9134282591440216\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "68aae8aed62f44e9889ae612ce33b607"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.13691375 -0.02894331  0.09065074  0.08823393]\n",
            " [ 0.22690888  0.04687278 -0.01866214 -0.00554652]\n",
            " [ 0.18976693  0.10489112 -0.02635139  0.01030673]\n",
            " [ 0.15997895 -0.00508536  0.07314872  0.0019685 ]\n",
            " [ 0.16047646  0.02576755  0.04630897  0.02371189]\n",
            " [ 0.09780377 -0.050104   -0.0612296  -0.03089226]\n",
            " [-0.16414224 -0.01682771 -0.0385286   0.05013207]\n",
            " [-0.12692735  0.02577768 -0.02754582 -0.01229728]\n",
            " [-0.14074355  0.03369103  0.05690824 -0.04195264]\n",
            " [ 0.1482247  -0.02325317 -0.03687579  0.03812365]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb98275a10>\n",
            "Shape values [0.08823393 0.09065074 0.10489112 0.22690888]\n",
            "Shap values final [0.04144328 0.01127866 0.00578233 0.01217881]\n",
            "Coefficients: \n",
            " [[-0.19625 -0.0075  -0.005    0.005  ]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.97\n",
            "Evaluating classroom: Class 2 - STI\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb9828ca60>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.011420352992171142\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3e76878e8aaa46a1bf8058e7bd71294a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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gAezs7BAdHY3U1FSMGzcOGzduhIODg155sCeciIiIiCRhacH38+zt7TF27FiMHTtWku0zCCciIiIiSfCx9boxCCciIiIiSVhqT/jnn3/+0mVkMhlmzpxZ4jwYhBMRERGRJCztrij5Tpw4oZEmCAIePXqE3NxclC5dmmPCiYiIiMg8WWpP+IEDB7SmK5VK/PHHH1i/fj3WrFmjVx68OwoRERERScJS746ii42NDQYPHozg4GD873//02tbDMKJiIiISBICZKrXq8TX1xfR0dF6bYPDUYiIiIhIEq9KD3hhUVFRHBNORERERObJUi/MXLZsmdb01NRUREdH4+LFixg5cqReeTAIJyIiIiJJWGpPuK4g3M3NDZUrV8a3336Lfv366ZUHg3AiIiIikohlBuGXLl2SPA8G4UREREQkiVftgkxDYhBORERERJKwlOEod+/eLdF6FSpUKHGeDMKJiIiISBKWcmFmmzZtIJMV/wdDXFxcifNkEE5EREREkrCU4SgzZ84sURCuDwbhRERERCQJSxmO0rt3b6PnySCciIiIiCRhKcNRTIFBOBERERFJQoDc1EXQy6lTp3Dx4kWkpqZCEAS1eTKZDOPGjSvxthmEExEREZEkLLUnPDk5GaNGjcLZs2chiiJkMhlEMW9v8v83SRAeExOD0aNHq6XZ2trCw8MDDRs2xNChQ1GtWrUSF4qIiIiILJ+ljAkvbM6cObh8+TLmz5+PunXrol27dli9ejUqVaqEdevWITY2FqtWrdIrD716wjt27Ijg4GAAQFZWFq5evYqwsDAcOHAAmzZtQvny5fUqHBERERFZLksNwg8fPox33nkHXbp0wdOnTwEAcrkcVatWxfTp0zF+/HjMnDkTCxYsKHEeegXhvr6+6NKli1palSpVMG/ePBw4cACDBg3SZ/OW41k6cOoG4FMBqFjG1KUhMooLj0UkKYBmFQBruWUeZC2FIIo4cQ+wtwIavFG0un6cIeLMIxF1PWTwcOT7o02GUsTfd2RQZtrCz9SF0dOTTBGxD0UElJXhjfRnwLlbQP1qQBkX7StkK4HjV4ByboBvJc35ggBEXQIc7fK2Y0z8Tn2lWOpwlJSUFNSsWRMA4OTkBABIT09XzQ8ODsbChQv1ysPgY8LLli0LALCxsTH0ps3T9uPAkCVAugKwkgNf98t7Eb2isnNF9NslIOxa3qG1igsQ/rYV/Mow0JNCYqqIDltyEZeUN92yEvBnbyu42Oqu71VnBUzYLyArF7C1Aha1lmNMfcu+OMrQDt4S0GengKcKG8jgi9HpAn7saOpSlcy68wLGRApQ5AATo8Kx4M9fYKXMAextgR8+AIa3VV/hzE2gy/8Bd/9rVO8EAxs+AqysAAA295/BfuBnwJV7efNbBwC7vgCc7KXfmdBjwLtLC75Tv3kHmNZX+nxJMpZyn/DCypUrh8ePHwPIG3JdpkwZXLp0Ce3atQMAPHjwQO/7iut1VFYoFEhOTkZycjLu37+Po0eP4scff0SpUqXQpk0bvQpmEbKUwMjleQcLAMgVgOmbgEuJpi0XkYR+uSCqAnAAuJUKTDoovGAN0sdXRwRVAA4AhxOBJad19y09yRQx8UBeAA4A2bnARwcFPEy31P4owxNFER/sE/D0v0O3CBl+OmeFI4mWV0fJChHj/gvAPVOeYl7Y+rwAHAAU2cD4VcDTNPWVJqwuCMAB4I+jwJZjqsmKPxyCPD8AB4CD54FleyTci/8osoGRP6l/p369CbhSsseJk3kQIVO9LElQUBCioqJU0507d8bq1avx008/4YcffsD69evRpEkTvfLQqyd8xYoVWLFihVpa9erV8fPPP6t6xM1BVlYWcnNzDb5d2eW7cHicopnfkYvIrVLa4Pk9LzMzU+3v6471oU7K+jiWaAXASi0t+r6AjIwsg+dlCJbeNk7ctUbh/pLjd3KQkZGjdfnoOzIoctTPRGbnAicSFWjpmQ17+7zeTIVC8fqcsSzkiQK4nmyrkX7kVhYalrasH5Sn7smQ8d/7Xf9uPGyEQt91mdlQnLoKobmPKsnh5FWNcEgZFQflWw2RmZkJp4v3UFjO8cvIzsgwdPHVyC4mwiGp0A8GUUTW0YvIrVRK0ry1seRjh6Ojo6mLoGJpwXe+YcOGISoqCtnZ2bC1tcWECRNw7do1LF68GEBekD5t2jS98tArCO/Vq5eqWz47Oxs3btzAhg0b8OGHH2L58uVmc2Hm+fPnJdmuLDsHdUo5wiZZ/cB01V1EVlycJHkWFh8fb5R8LAXrQ50U9VEhtzSAymppPo6piIu7afC8DMlS20ZNu8qIg/qP+sp4gLi4h1qXt1FawU7ujyyhIHC3kQmwT7qCa2k5qF69OgAgMfH1PWMnikAlB18kZtqppXtkxiMuLl3HWubJSimHvdwfCsEKsRW8oJRbqQXigp01LlmlI/e57yRvf0+4/HtbbTu3Pe3w9L9lvPzLwz7hidr8+5Wc8UDi7zVZdg7qujnA+llB0CvKgKtugtG+U7WxxGNHo0aNTF0EFcv6WVvAx8cHPj4FP17d3Nywbt06pKSkQC6Xw9nZWe889ArCq1SpotYV36JFCzRq1AjDhg3DkiVLMGvWLL0LaAgBAQGS9IQDgPDTBxBHLIcsPQuilRzKz3uheucWkuT1vMzMTMTHx8PLywsODg6S52fuWB/qpKyPGt5AbLaAP2/mBXlVXEQs62gPH3fzvLTN0tvG/MrAtV0C4p7m1XdIBQHT25aBi63uC9bmWwuY/I8MWbky2MpFzAkREBxQC0qlEvv27UP16tVRqVIluLjouGjvNbDSTYZB4SKeZskgg4iR/tkY0KyKqYtVIotsRXz0t4j7ru6Y0mMo5v35K6yVORDtbaBcMAzeTRqqLS/7cTSE3vMgv5d3x4ect5vCc0JveFrJkZmZiTvjWqHU1cewunYfAJDb0h+lvx6E0kYYE5774wewGrmi4Dv1y96o3ilE8ny1sfRjh7kQLfTC/WvXrqkuzHyeq6urwfIw+IWZAQEBcHZ2RkxMjKE3XWJ2dnYvX6ik+r8JdAkCYq5D5lMBthXLQPMkp3QcHBzM6rSTqbE+1ElRH44AdvUpfHcU8x/WYKlto5YjcH7483dHsQZecpQZFwi84y/i7GMRdcrK4OGY9/4olUooFHnjbe3t7S2yPgylcy0g0UvE3/EK5Dy4irYNa1psfYxqCLztl3c3nNpjusE6vQVw/jZk9bxgp+3uKE39gPjlqrujWPtWUgsGlJ5uyPp3DhzP3QEcbGFVvxqMVjMDWwFdg4BTN0zynaqNpR47zIVomTE4unXrhlq1aqFr167o3LkzqlatavA8JHliZm5uLpRKpRSbNk+ujkCbOqYuBZFR1S5roUdWCySXydCsQvHWKesoQ5sqfI9exNFGhjcriohLsfzvqzIOz73fTqWANqVevIKtDdCytu75cjnQzEf3fCm5OfE79RUiWFvmceibb77B3r17sWTJEixevBh+fn7o0qULOnfujIoVKxokD4Pfs+r48ePIzMyEr6+voTdNRERERBZEtJKpXpakf//+WL9+PQ4fPowvv/wSDg4OmD9/Ptq1a4d33nkH69evx4MHD/TKQ6+e8EuXLmHPnrzbFuVfmLl9+3ZYW1tjzJgxehWMiIiIiCybYKFjwvOVLVsWgwcPxuDBg/HgwQPs3bsX4eHhmD17NubMmYMLFy6UeNt6BeERERGIiIgAkPcoTzc3NzRt2hTDhg1D7dovOM1FRERERK888RV6TpiHhwdq1aqFK1eu4MqVK3rfvrJEQXhgYKBZXXhJRERERObHUu+Okk8URZw4cQJ79uxBZGQknj59CldXV3Tt2hVdunTRa9uSXJhJRERERCRY2FjwfDExMdi7dy8iIiLw5MkTODs7o127dujcuTOaN28Oa2v9Q2gG4UREREQkCcEyY3AMHjwYjo6OaN26Nbp06YIWLVrA1tawN8xkEE5EREREkrDU4SiLFy9Gq1atJH3WDINwIiIiIpKEpT6sp2PHjpLnwSCciIiIiCQhyiw0CjcCBuFEREREJAlLHRNuDAzCiYiIiEgSlnp3FGNgEE5EREREkuBwFN0YhBMRERGRJDgcRbdX6GGiRERERGRORJlM9bI0aWlpWLlyJd5//3307NkTZ8+eBQAkJydj7dq1SEhI0Gv77AknIiIiIklY6i0K79+/j8GDB+P+/fuoWrUqbty4gfT0dABAqVKlsGnTJty5cwfTpk0rcR4MwomIiIhIErkW+rCeOXPmID09HTt27EDp0qXRvHlztfnt2rXDoUOH9MqDw1GIiIiISBKWOhzl6NGjGDJkCGrWrAmZlrJXrlwZ9+7d0ysP9oQTERERkSQsLfjOp1AoULp0aZ3z84em6IM94UREREQkCVFW8LIkNWrUQHR0tM75kZGR8Pf31ysPBuFEREREJAlRLlO9LMm7776LPXv2YOXKlUhLSwMAiKKIhIQETJkyBbGxsRg2bJheeXA4ChERERFJwlKHo/To0QN3797F4sWLsWjRIgDAiBEjIIoi5HI5Pv74Y7Rr106vPBiEExEREZEkRCvLHXQxZswY9OjRA/v27UNCQgIEQUCVKlXQoUMHVK5cWe/tMwgnIiIiIklY2jAUAMjMzMSgQYPQt29fDBgwQO9hJ7owCCciIiIiSVjicBQHBwckJiZqvTWhIVnuOQIiIiIiMmuiTK56WZIWLVrgyJEjkuZhWTVCRERERBbDUu+OMnbsWMTHx2PKlCmIiYnBgwcPkJycrPHSB4ejEBEREZEkLC34zte1a1cAwLVr1/Dnn3/qXC4uLq7EeTAIJyIiIiJJWOKYcAAYN26c5GPCGYQTEVm63THA4t2AQgkMaw0Mb2vqEhERAbDcnvAJEyZIngeDcCIiS3boPNB9FiCKedP/XARyBeCD9qYtFxERLLcn3BgYhBMRWbLV+wsC8Hyr/mIQTkRmwVKD8GXLlr10GZlMhnHjxpU4DwbhRESWzFrLTa6srYxfDiIiLQS5Zd6I70VBuEwmgyiKDMKJiF5rozoAvx0GcnIL0sZ3Nl15iIieY6k94ZcuXdJIEwQBd+7cwcaNGxEdHY1Vq1bplYfeP09SUlIQHByMwMBA7N69W9/NERFRcTT1AQ59B/QPAXo0BrZ/BgxsaepSEREByAvC81+WTi6Xo3Llyvjss89QtWpVzJgxQ6/t6d0TvnfvXmRnZ6NixYrYuXOn6r6KRERkJMF+eS8iIjNjqXdHeZmgoCDMmzdPr23o3RMeFhaGwMBADBgwAKdPn0ZiYqK+myQiSyMIBf8WvkiQjOe596FEq5vZe5dfHl3lMrfyWjKD1qWe7ZBeLa9ST/jzzp8/D7me49316gm/dOkSrly5gm+++QYhISFYtGgRdu7cibFjx+pVKCKyEAfOARN+Bi7exsN63hjQfSQOlaqCrtVl+LmDHOWcXq2Drtnacwr4aA1w9R7Q0h9YPQ6oWb7Iq6dmixjzl4DNl0W42QFfNJHj40DTXUz1VCFi5D4B26+KkMsApQDULgMsaytHqypyLIgRMOuEgGdZQD8fGX5qL4eLLdtaSaw5J+CrowLupwPda8iwuIUeG4u6BIxdCZyJBwJrAMtHA41qGKqoZKEsNfjesWOH1vSUlBTExMRg37596Nu3r1556BWEh4WFwdHREW3btoWDgwNatGiB3bt3Y/To0Xr/OiAiM5ecDvSYBaQpAADlzlzBisS58P50MXZdl2PEPgE7e/EuHZK7/xToPQfIUuZNH74IvD0XiF1Q5E18ckjAhri8ntDHmcCkQwJ8SwOdq5vmOD5+v4CtV/LKk/tfB+2FJ8BbOwSs6Shi8qGCXtsNcSJcbAX81J5trbhi7osYESEgvzbDrokQc63xtVcJNpaRBXSfCSSl/bfx68Bbs4D45YAN7wHxOrPUu6NMnTpV5zx3d3eMHDlSrzujAHoE4VlZWQgPD0ebNm3g4OAAAOjatSsOHjyIY8eOITg4WK+CGVJWVhZyc3NfvqAFyczMVPv7umN9qDNGfVjtjYHdfwF4vppPHqD2g0ScL18Fu28ISE3LgpWJj7+vetuw2nkCdvkBeL4z8ci8dAtilbJqyUqlEvb29gAAhUIBGxsbAMCOqzYA1Hurtl1W4k1P0xw3w7SUBwBSs4Hl/+YAUA+4d1wVMD84q0R5vert40VCL1lBLFSXu+Nl+Kpq8etDHnkO9vkBeL67SVAcuQChSS19i2oSltw2HB0dTV0EFUvtCd+/f79Gmkwmg6urK5ydnQ2SR4mD8IMHDyI1NRXdunVTpYWEhMDd3R07d+40qyD8/Pnzpi6CZOLj401dBLPC+lAnZX04Zj9D4UsBlXIrPHBxAwCUtVXiyuU4yfIvrle1bbjkpsG7UJpgZ41LDxMhpD/SWL569eoAoHb9ThnrWngI9S9t64yHiIt7aPDyFkVZWx+k59hrnecmPAWg/uOitFUm4uKu6pXnq9o+XkSeWhpAZbU0D1slZLLi14d91lPULpQmyoCr6U+QHZejVzlNzRLbRqNGjUxdBBVLDcJlMhlKly6t6rgoTKFQICkpCRUqVChxHiUOwsPCwuDu7o5y5crh9u3bqvSmTZsiMjISycnJKFWqVIkLZkgBAQGvZE94fHw8vLy8VGciXmesD3VGqQ8/P+RsOQvr3adVSYtDOuORsxtkEPFtczn8/Ex/x45Xvm34+iJ38xlYHbqgSsqZ0gM+gfU1FlUqldi3bx+qV6+OSpUqwcXFBQAww0GGd8JF5Ah5X5ZVXER89mYZlHMsY4w90DDDRoZ3/xIhiOpf3m9VEzD/TVdEbxVxOy1vnrVcxP9a2sCvasna2ivfPl7gw5rA9kcC4pLyTlfJIOKrxnkBc7Hrw88POf3Ow3pzlCopZ3gb1GjT1KBlNqbXuW0YkmiZMTjatm2LOXPmoHv37lrnHzhwAJMnT0ZcXMk7m0oUhN+5cwcxMTEQRRG9e/fWusyePXswcODAEhfMkOzs7ExdBMk4ODiY1WknU2N9qJO8PnZ8Duw4AZxNgKKJL0pVrofpqSK617BCI08b6fItgVe6beybDmw9BsQlAm3qwLZVAGy1LKZUKqFQ5A0hsre3V9VHb3/g7BsiQq+IcLcHBvnJUMredO/f4LpAvfIitl8V8ThThIOViKDycvSqZQUruS3ODBOxMU7EUwXwtrcMvmX0L+sr3T50cARwcrCI3y+JuJsGvFVDBh8Xa8TFlbA+fp8EDGgBnL4BNKkFmy6NYGOhvaDPex3bhiFZak+4+JI7BimVStPcHWXXrl0QRRHTpk3TOi7mp59+ws6dO80mCCciiVhbAW83B95uDnsAI0xdnteVjXVe8KMHvzIyTGtmPl+WdTxkqOOhvTzu9jKMa2A+ZbVkzrYyfFC3oC4zMvTYmFwO9GyS9yL6T64FXZiZlpaGlJQU1XRycjLu3r2rsVxKSgr27NkDDw8PvfIrdhAuCAJ27dqFmjVromfPnlqXuXHjBlauXIkLFy6gdu3Co8SIiIiI6HUgarnI2lytW7cOP/zwA4C8MeEzZ87EzJkztS4riiI++ugjvfIrdhB+/PhxPHjwAD169NC5TJs2bbBy5UqEhYUxCCciIiJ6TVnScJTg4GA4OjpCFEXMnTsXXbt21YhjZTIZHBwcULt2bdSpU0ev/IodhIeFhQHIC7R1qVmzJqpUqYJ9+/Zh0qRJOq8sJSIiIqJXlyUF4Q0aNECDBg0A5F2Y26FDB3h7F77/lOEUOwifPXt2kZbbtm1bsQtDRERERK8OSwrCnzd+/HjJ8+BjrIiIiIhIEpZ6i8J8p06dwsWLF5GamgpBENTmyWQyvZ6aySCciIiIiCRhSXdHeV5ycjJGjRqFs2fPQhRFyGQy1W0L8//XNwi3zJohIiIiIrMnymSqlyWZM2cOLl++jPnz5yMyMhKiKGL16tWIiIhA//794efnh3/++UevPBiEExEREZEkBJlM9bIkhw8fxjvvvIMuXbrAyckJACCXy1G1alVMnz4dFStW1Hn7wqJiEE5EREREkhBlBS9LkpKSgpo1awKAKghPT09XzQ8ODsaRI0f0yoNBOBERERFJQoRM9bIk5cqVw+PHjwEAtra2KFOmDC5duqSa/+DBA8j07N3nhZlEREREJAlLvTAzKCgIUVFRGDNmDACgc+fOWL16NaysrCAIAtavX48WLVrolQeDcCIiIiKShKVdkJlv2LBhiIqKQnZ2NmxtbTFhwgRcu3YNixcvBpAXpE+bNk2vPBiEExEREZEkBMuMweHj4wMfHx/VtJubG9atW4eUlBTI5XI4OzvrnQeDcCIiIiKShKX2hOvi6upqsG1Z5kAdIiIiIjJ7AmSql6W5e/cuvv76a3Ts2BGNGzdGdHQ0ACApKQkzZszAxYsX9do+g3AiIiIikoSlPqzn2rVr6NWrF/bu3YtKlSohNTUVOTk5AIDSpUvj1KlT+O233/TKg8NRiIiIiEgSOXLLCr7zzZ07Fy4uLti8eTMAoHnz5mrz33zzTezdu1evPNgTTkRERESSsNSe8OjoaAwYMAClS5fWej/wChUq4MGDB3rlwZ5wIiIiIpKEpd4dRRRF2Nvb65yflJQEW1tbvfJgTzgRERERScJSn5jp7++Pv//+W+u8nJwc7N69G/Xq1dMrDwbhRERERCQJQSZTvSzJyJEj8c8//2D69Om4evUqAODJkyeIiorC8OHDcePGDYwcOVKvPDgchYiIiIgkYakXZr755puYNWsWZs6cqbo4c8qUKRBFEc7Ozpg9ezaCgoL0yoNBOBERERFJwhLvD56vZ8+e6NChA44ePYqEhAQIgoAqVaogJCSET8wkIiIiIvNlSXdFWbBgAbp06QJfX19VmqOjI9q3by9JfhwTTkRERESSEGQFL3O3cuVK1fhvAHj69Cn8/Pxw7NgxSfJjTzgRERERScLSLsgsTBRFybbNIJyIiIiIJKG08CBcSgzCiYiIiEgSlt4TLiUG4UREREQkCUsYC/68O3fu4MKFCwCA1NRUAEBCQgJcXV21Ll+7du0S58UgnIiIiIgkYWm3KFy8eDEWL16slvbtt99qLCeKImQyGeLi4kqcF4NwIiIiIpJErgUNR5k1a5ZR82MQTkRERESSsKThKL169TJqfgzCiYiIiEgS2RbUE25sJQ7CFQoFtm3bhgMHDuDGjRtIT0+Hm5sbfH190b59e3Tu3BnW1ozxiYiIiF5XvDuKbiWKkm/fvo0PP/wQt27dQuPGjTFs2DCUKlUKSUlJOHnyJL799lvcuHEDH374oaHLS0REREQWwpLGhBtbsYNwhUKBjz76CHfu3MGcOXPQpk0btfnDhg3DhQsXcPHiRYMVkoiIiIgsT46pC2DGih2E79ixAwkJCXj33Xc1AvB8tWvX1uu+iURkQe4mATNDgbMJQLAv8HlvwNWxSKuefyTi+5MCElNFvFVTjg8bymAll6bXxCr0OLDhCGBrDUzoArSvL0k+haVkiZh1QsDRuyLqlpXhy6ZylHd+NXqGEp6J+L8TAi4liWhdWYbPGsvhaFOyfVtzTsDGOBFudsCkQDmCK2rfjiCKWPaviO1XRZR3Aj5tLEf9cjLg+n1gVihw5R7Qvi4wpSdgb6vH3mlS5opYeErE7hsCvFxlmNpEDr8yZvJertkPbPwHcHMEJnUHgv1MXSIiAOwJf5FiB+EHDhwAYPwrSInIDOXkAq2/Bq7czZv+5yIQfQ2I/Oalq95NExGyKRfPsvKm/04UcDtVhoWtrQxezNJ7zsHu650FCbtPAwe+Bd6UvrOgV5iAA7dEAMA/iSIib+Xi/DArWEv0Y8NYMpUiWmzKxe28Z1ngn0QR5x8LCO1R/Pdv8SkBHx0UVNN/3sjFiUFWecF1IdOOCJh1QlRN77qeiwt9slEl5AvgfvJ/hbkIXLoDbPi42GV5kYkHBCw/k5f3YYj480YuLg23goejid/LxX8CH60pmP4zBjgxG6hfzXRlIvqPgkG4TsUOwq9fvw4nJydUqlRJivJIIisrC7m5uaYuhkFlZmaq/X3dsT7UGas+5PvPwT4/AM+3/ywyz96AWNPzheuuPyvHsyz1Q9DKMwL+1zgLhoxPMzMz4RF6Wj1REJDzwx5kB0kbpFxLBg7cUu+NvZwE7L2qQNvKovaVJKRUKmFvbw8gb2ihjY1Nibe1/boMt1PV199+VcDNx1l4o2gnQlR+/NcGeO6BHtm5wMp/szGvheZxe3ms+rJpSiD6p6Ookh+A/0f84ygy5w4GSjm9MO+iflaycoG159XzTlIAv53Lwqg6gu4VjcD+x72QP5+QnQPlyggo5w0t9rZ4LC1gyXXh6FjMD6GElIzBdSp2EJ6WloYyZcpIURbJnD9/3tRFkEx8fLypi2BWWB/qpK4Pl1u34K0l/fr168hSPn3hug8feACooJYmCALi4uIMGoQDgI+WtJSUFNzU40lnRXErwxaA5rCAW7duIS4tTdK8dalevToAIDExUa/tJD50A+ClkX716lUk2RZvFGhWtg8Ae7W0pKQkxMXd1Vg2N7c2Cn91pfz3aGl1Iq5cuYJcF3st8zS97LOSLcggigFAoaf/3b9/H3HWT4qUh1RqZ2Wj8F4+TUrCbT3aN4+lBSyxLho1amTqIqgo2ROuU7GDcGdnZ6Snp0tRFskEBAS8kj3h8fHx8PLygoODg6mLY3KsD3VGq49a3hAWH4T86n1VUm6r2qjeMfilq46vAqy9LeJZdsEB+v0AoLa/YceyZmZm4lGfhnA+UxB0inIZHD/uCT8/acfN+gF4M1HA33cK+im9S4kY0qwyrOW615OKUqnEvn37UL16dVSqVAkuLi4l3pZXLWBZgojEtIL3763qIkLq1Sr2tsZly/Hp0YJpW7mID4NLwa+sm8ayI5/JMO+5ExvONiKCP3wT4uZdkD14pkrP7dMM3o0bvDTv4nxWhj4W8fOFgunSdiLGhpSDh0O5l+YjJfm4zsCnv6mmRVtruHzYC35+VYu9LR5LC7AuDENp6gKYsWIH4TVq1MDp06eRmJhoMUNS7OzsTF0EyTg4OJjVaSdTY32oM0p9/D0D+L+CCzOtPu9dpDxrOAJHBoiYHS3gdkr+hZlWklyYGd+lDip4VYHdhiOAnQ1k4zvD3kgXZu7sXXBhZj0PGb5oYgVX55IPA9GHUqmEQqEAANjb2+vVNhyR9/7NPCEgLklEm8oyfNrYBo42xb8YckozoKyzgA1xIkrZAR8HWqFZRe11NLu1iCqlRGxTXZhpBe9yZYCjs/IuzLx6D2hfD9ZTesLaruj1XJTPyo8dRNQqI2LPDQFVXWWY2sQKVcuY5r1UM6U3UNYN2PAPUMoRso+7w6GZfj8weSwtwLrQTwZ7wnUqdhDepk0bnD59GmFhYRg3bpwUZSIiS1K+NLDsgxKtGuAhw69dDH8hpja5fZoCQ7Tf0UlKrnYyzGppnH00tqpuMqzoYJh9e6+OHO/VeflycpkMExrKMKFhoRk1PIGfpf1OsrGS4dPGMnza2ASnMV7mvbZ5LyIzk8kYXKdiH0l69uyJqlWr4tdff8WhQ4e0LhMXF4ctW7boWzYiIiIismDZMpnqReqK3RNub2+PRYsW4cMPP8Qnn3yCpk2bokmTJnBzc8PTp09x6tQpHDt2DEOHFv+qbCIiIiJ6hTD41qlEj62vXLkyNm7ciNDQUBw4cABr1qxBRkYG3Nzc4Ofnh2+++QadOnUydFmJiIiIiF4JJQrCgbwe8UGDBmHQoEGGLA8RERERvSrYE65TiYNwIiIiIqIXYgyuE4NwIiIiIpIGe8J1YhBORERERNJgDK4Tg3AiIiIikgijcF0YhBMRERGRNBiD68QgnIiIiIgkwihcFwbhRERERCQNxuA6MQgnIiIiImnw7ig6MQgnIiIiImkwBteJQTgRERERSYM94TrJTV0AIiIiIqLXDXvCiYiIiEga7AjXiUE4EREREUmDw1F0YhBORERERNJgDK4Tg3AiIiIikgijcF0YhBMRERGRNBiD68S7oxARERERGRl7womIiIhIGuwJ14lBOBERERFJg3dH0YlBOBERERFJgzG4TgzCiYiIiEgijMJ1YRBORERERNJgDK4T745CRERERGRk7AknIiIiImmwJ1wnBuFEREREJA3eHUUnBuFEREREJA3G4DpxTDgRERERkZGxJ5yIiIiIpMGecJ0YhBMRERGRNDgmXCcORyEiIiIik1m6dCkaNGhg6mIYHXvCiYiIiEga7AjXiT3hRERERERGxiCciIiIiKQhe+5VQpcvX8b777+P+vXro1GjRpg4cSLu3r2rmv/FF19g4MCBqumkpCT4+vqiT58+qrT09HTUrl0be/fuLXlBDIxBOBERERGZpXv37mHw4MF4+vQp5s6di2+//RYXLlzA4MGDkZaWBgAICgrCuXPnkJWVBQCIiYmBra0t4uLiVMv8+++/yMnJQVBQkMn2pbBXfkz45cuXkZ2dbepiGJwoigCAa9euQcYrj1kfhbA+CrAu1NWsWRMAEB8fD7mc/TBsH+pYHwUsuS5sbW3h4+Nj6mLkketXd+vWrUNOTg7WrFmDUqVKAQD8/PzQtWtXbN++HUOGDEFgYCCys7Nx5swZNG7cGNHR0Wjfvj2OHDmC06dPo2XLloiOjoaXlxfKli1rgJ0yDB6BLdTDhw/x9OlTizswSIX1oY71UYB1oS49PR1Pnz5lAP4ftg91rI8CrAvDED+xVr1KIiYmBk2aNFEF4ABQo0YN+Pr64tSpUwCAypUrw9PTE9HR0ap1GjdujMDAQLU0c+oFB16DnnCz+SVoYNOmTQMAhIWFmbgk5oH1oY71UYB1oY71oY71oY71UYB1YR5SUlLg5+enkV6mTBk8e/ZMNR0UFISYmBikpaXh0qVLCAwMRGZmJsLDw5GdnY2zZ8+ib9++xiz6S7ErhIiIiIjMkpubG548eaKR/uTJE7i5uammg4KCEBsbixMnTsDd3R01atRAYGAgzp8/j+PHjyM7OxuBgYHGLPpLMQgnIiIiIrPUqFEjHD9+XK3X+8aNG7h8+TIaNWqkSgsMDERGRgbWrVunCrb9/PxgZ2eHVatWoXz58qhUqZLRy/8ir/xwFCIiIiIyb7m5uQgPD9dIHzp0KLZt24bhw4djzJgxyMrKwqJFi1C+fHn06tVLtVyNGjVQpkwZnDx5UjWUyMrKCg0bNsThw4fRvXt3o+1LUTEIJyIiIiKTysrKwocffqiRPmfOHPz666+YM2cOPvnkE8jlcgQHB2Pq1KlwdnZWWzYwMBARERFqF2AGBQXh8OHDZndRJsAgnIiIiIhMaMKECZgwYcILl1mzZs1Lt7NkyRKNtJEjR2LkyJElLpuUOCaciIiIiMjIZGL+3eiJiIiIiMgo2BNORERERGRkDMKJiIiIiIyMQTgRERERkZExCCciIiIiMjLeotBMHD58GD/99BMSEhLg6emJYcOG4a233nrhOkqlEj/++CPOnz+PuLg4KBQKREZGolSpUhrLnjlzBosWLcKVK1fg7u6Ot99+G++++y5kMplqGVEUsX79emzZsgXJycnw9vbGpEmTUKdOHUPv7guVpC4AIC0tDQsWLMChQ4eQk5ODpk2b4tNPP0XZsmVVy3Tv3h337t3Tuv7atWtV+6pruaNHj8LOzq6Ee1YyUtbHihUrsGrVKo11p06dirfffls1bS5tA5C2PkJDQ3HgwAFcu3YNCoUC1apVw7Bhw9CqVSu1bRm7fcTHx2POnDk4e/YsnJyc0KVLF4wdOxY2NjYvXK+o79ujR48wZ84cnDhxAtbW1mjdujU+/vhjjXvwlrTuDU3K+jhx4gR27NiB8+fPIykpCRUqVED37t0xcOBAWFsXfGV+8803+PPPPzXyWLJkCZo3b264nS0CKesjJiYGo0eP1li3ffv2mDVrllra69A+dL3vADB+/HgMGzbshcuZon2Q+WIQbgZiY2MxZcoU9OjRA5MnT0Z0dDT+97//wdHREe3atdO5nkKhwI4dO+Dv748GDRrg2LFjWpe7ffs2JkyYgCZNmmDMmDG4evUqli1bBisrKwwZMkS13Pr167FixQqMHz8etWrVwpYtWzB+/Hhs2LDBaI96LWldAMDnn3+OGzdu4PPPP4etrS1+/PFHTJw4Eb/88ovqy3Pu3LlQKpVq6y1duhQ3b96En5+fWnrbtm0xePBgtTRbW1sD7GXRSV0fAGBnZ4fly5errVuxYkW1aXNoG4D09bFmzRo0a9YMb7/9NhwcHLB//3588skn+Oabb9CtWze17RmrfaSkpGD06NGoUqUK5s6di4cPH2LhwoVQKBT47LPPXrhuUd63nJwcjB8/HgAwY8YMKBQKLF68GNOmTcOiRYtU29Kn7g1J6vrYtm0bFAoFRo0aBU9PT5w/fx4rVqzAzZs3MX36dLXtVaxYETNmzFBLq1atmmF3+CWkro9806dPh5eXl2q6cGfP69I+RowYgT59+qitt2/fPvz+++8awbU5tA8ycyKZ3Lhx48T33ntPLe2LL74Q33777ZeuKwiCKIqiuHPnTrFRo0bi06dPNZaZMWOG2K1bNzE7O1uVtmzZMrFVq1ZiVlaWKIqiqFAoxJYtW4rLli1TLZOdnS1269ZNnDVrVkl2q0RKWhdnzpwRGzVqJB47dkyVdvPmTTEwMFDct2+fzvUyMjLEkJAQ8fvvv1dL79atm0aaKUhdH8uXLxdDQkJeuC1zaRuiKH19aPv8jB07VuzXr59amjHbx5o1a8SQkBAxOTlZlRYaGio2btxYfPjwoc71ivq+7d27VwwMDBRv3rypSjt27JjYqFEj8dy5c6o0fY5ThiR1fWhrA6tXrxYDAwPV5k2fPl3s27evfjtjAFLXR3R0tNioUSPxwoULLyzH69I+tPnggw802oK5tA8ybxwTbmLZ2dmIiYnR6Cno0KEDbt68ibt3775w/eeHk+gSFRWFVq1aqZ2K69ChA1JTU3H27FkAwNmzZ5Genq5WDhsbG7Ru3RpHjx4tzi6VmD51ERUVBRcXFzRp0kSV5uXlBW9v7xeW/++//0ZmZiY6deqk/w4YmCnqQxtzaBuAcepD21AuHx8fPH78WP8dKKGoqCg0btwYbm5uqrT27dtDEAQcP35c53pFfd+ioqJQq1YttV7OJk2awM3NTbWcvscpQ5K6PnS1AVEUTdoOdJG6PoridWofhT18+BCxsbFm+R1C5o9BuIklJiYiJydH7QsQKDhlFR8fr9f2MzMz8eDBA1StWlUt3cvLCzKZTLX9/L/aynH//n0oFAq9ylEU+tRFfHw8qlatqvGjpFq1ai9cLzw8HBUqVEC9evW0zmvWrBlatGiBiRMn4tq1a0XeF0MwVn1kZWWhXbt2aNKkCfr27Yvt27drbAswbdsATNM+gLzT7IXzBIzXPuLj4zXyd3FxQdmyZV+6z8DL37f8unmeTCZD1apVVduQ+jhVHFLXhzaxsbGwtbVFhQoV1NITExPx5ptvomnTphg8eDAOHTpUjD0xDGPVx4cffojGjRujS5cuWLx4sdr817l9REREQBAEdOzYUWOeObQPMm8cE25iKSkpAPIOEs9zdXVVm19SqampWrdvY2MDe3t71fZTUlJga2urcVGZi4sLRFFEamoq7O3t9SrLy+hTFykpKRrr5W9L13rJyck4fvy42rj4fC1btkRAQAA8PT1x584drFmzBu+//75Rx0Aboz4qV66MCRMmwMfHB9nZ2QgPD8f//d//IS0tTVUv5tA28suRn+/zpGofQF6gffbsWcybN08t3Zjto6RlL+r7lpqaqnX7rq6uaseH/HULL/P8fGOQuj4Ku3XrFjZt2oQ+ffrA0dFRle7j4wN/f39Ur14daWlp2Lp1Kz755BN8//33Rh8DLWV9ODs7Y+jQoWjYsCHs7OwQHR2N3377DTdv3lRdM/A6t4/w8HDUrVtX4zoac2kfZN4YhEsgLS2tSKctC39oX0XmXBeRkZHIycnR2oMxZcoU1f8NGjRA06ZN0adPH/z222+YOnVqifM0t/ro0qWL2nRISAiUSiVWr16NAQMGqF3AKQVzq4/nXb16FbNmzUL37t017o4iVfsg85KWloYpU6agQoUKGDt2rNq8AQMGqE23bNkSw4cPx4oVK16pIMvX1xe+vr6q6aCgIJQtWxZz5szB+fPnERAQYMLSmVZ8fDwuX76sdjzI97q0D9IPg3AJREZGalwRrc3WrVtVPQVpaWlq8/J/sefPL6n8HoHC21cqlVAoFKrtu7q6Ijs7G1lZWWo9AampqZDJZFp7ForCWHXh6uqKBw8eaKSnpqbqXC88PBy1atVCzZo1X1q+smXLon79+oiLi3vpsi9izvWRr3379ti/fz9u376NatWqSdY2APOtj3v37mHixImoXbs2vvzyy5eWz1DtQxtXV1eNfQZe/l4W9X1zcXHRuv2UlBS88cYbqm0B0h2nikPq+sinVCoxZcoUpKamYs2aNXBwcHhhueRyOdq0aYMlS5ZAoVAY5ewQYLz6eF779u0xZ84cXLp0CQEBAa9l+wCAvXv3wsrKCh06dHhpuUzVPsi8MQiXQM+ePdGzZ88iLZudnQ1ra2vEx8ejWbNmqnRd49OKy8HBAW+88YbGWLiEhASIoqjafv7fhIQEeHt7q5XD09OzxAcMY9WFl5cXTp48CVEU1cb9xsfHaw2y79+/jzNnzmDcuHFFKpuhmGt9vIhUbQMwz/pITk7G+PHj4e7ujjlz5kh+NuBlvLy8ND6/+WcQXrbPwMvfNy8vL43x7KIoIiEhQXUha6VKlSQ9ThWH1PUBAIIgYNq0aYiLi8PPP/8MT09PQ+6CQRmjPl7mdWsf+SIiItCkSRO4u7sbouj0GuKFmSZma2uLwMBA7N+/Xy39r7/+QrVq1TQuBCqJ5s2b4/Dhw8jJyVGl7du3Dy4uLqoLEuvWrQsnJydERkaqlsnJycHBgwcRHBysdxmKQp+6aN68OVJSUnDy5ElVWkJCAi5fvqy1/OHh4QBQ5CvaHz16hNjYWPj7+xdpeUMwZn08LyIiAi4uLqhcuTIA82gbgHHqIyMjAxMnTkROTg6WLFmi8bAaXaRsH82bN8fJkydV13cAeWcQ5HI5mjZtqnO9or5vzZs3x9WrV3Hr1i1V2smTJ/Hs2TPVcsY4ThWV1PUBALNnz8Y///yD+fPnF/lHqyAIiIyMRPXq1Y3ay2mM+igsIiICAFTt/XVrHwBw/vx5JCYmah3OqI2p2geZN/aEm4ERI0Zg1KhRqgs2Tp06hfDwcI2nkTVp0gRdu3bF119/rUo7evQoMjMzcfHiRQB5TyxzdHRE9erVUb16dQDA0KFDER4eji+++AJ9+/bFtWvX8Ouvv6o9QczOzg7vvfceVq5cCXd3d9SsWRNbtmzBs2fPNB5IIqWS1kXdunXRrFkzfPfdd/j4449VD2OpVasWWrdurZFPREQE6tWrp7WHKzw8HEeOHEFwcDA8PDyQmJiIdevWwcrKyqh1AUhfH4MHD0a3bt3g5eUFhUKB8PBwHDx4EJMnT1b1AJtL2wCkr48pU6bg8uXL+Prrr3Hv3j21p2LmPzXP2O2jT58++OOPPzB58mQMHz4cDx8+xOLFi9G7d294eHiolhszZgzu3buHHTt2ACj6+9auXTusXbsWn376KcaNGweFQoFFixYhJCREbbxvUetealLXx5o1axAaGoohQ4bA1tYW586dU82rVq0anJ2dce/ePUyfPh0dO3ZE5cqVkZKSgtDQUMTFxWHOnDlGqwtA+vr46quvUKlSJfj6+qouzNy4cSNatWql9qPzdWkf+cLDw2FnZ6f1+8Wc2geZN5koiqKpC0F596su/LjfHj16qC0TGBiIbt264ZtvvlGl6Xp89gcffIBRo0apps+cOYOFCxeqHlvft29frY+tX7duHbZu3YqnT5+qHtlbt25dw+/wC5S0LvIfS37w4EHk5uaiSZMm+PTTT9UOvABw48YN9OvXT+PR7PnOnTuHZcuW4fr166o7RwQFBWHUqFFGPa2aT8r6+Pzzz3HhwgU8efIEAFCzZk30798fnTt3Vtu+ubQNQNr6CAwM1JlvTEwMANO0j5s3b2Lu3Lk4c+YMnJyc0LVrV43HcI8cORL37t3Drl27VGlFfd8ePnyIuXPn4sSJE7CyskLr1q0xadIkjTMBRal7Y5CyPkaOHInTp09rzXf58uUIDAzEs2fP8O233+Ly5ctISkqCjY0N/Pz8MGzYMLXhGMYiZX2sXbsWe/fuxf3795GdnY0KFSqgU6dOeO+99zQeA/86tA8AyM3NRZcuXdCwYUOtPzLMrX2Q+WIQTkRERERkZBwTTkRERERkZAzCiYiIiIiMjEE4EREREZGRMQgnIiIiIjIyBuFEREREREbGIJyIiIiIyMgYhBMRERERGRmDcCIiIiIiI2MQTvQamDp1Knx8fExdDADAlStX4O/vj6NHj6rSTpw4AR8fH2zbts2EJSNzsG3bNvj4+ODEiRMlWp9tSbu4uDj4+vri5MmTpi4KEf2HQThZrNu3b+Orr75Cp06dUK9ePQQFBaFz58747LPPcPz4cbVl27Rpg27duuncVn6QmpSUpHX+9evX4ePjAx8fH9Xjy7XJXyb/VadOHXTo0AGzZs1CcnJyifbzVfP999+jYcOGCA4ONnVRjCIxMRFLly5FXFycqYtCRpKSkoKlS5eW+IdESb2orfn5+aFdu3b4/vvvwQdlE5kHa1MXgKgkzp07hyFDhsDa2ho9e/ZEzZo1oVAokJCQgKNHj8LJyQlNmzY1WH5bt26Fk5MT7O3tERoaisDAQJ3L+vn54b333gMAPHv2DH///TfWrVuHqKgohIaGwtbW1mDlsjT//vsvjh49ih9++EEtPSgoCGfPnoW19at3SLpz5w6WLVuGihUrws/Pz9TFISNISUnBsmXLMH78eDRp0sRo+b6srb377rsYPHgw/v77b7Rq1cpo5SIi7V69bzx6Lfzwww/IzMxEWFgYfH19NeY/evTIYHkplUqEhYWhU6dOcHFxwebNm/Hll1/C2dlZ6/JvvPEGevTooZoeOnQoRo8ejYMHD2L//v3o3LmzwcpmaTZu3Ah3d3e8+eabaulyuRx2dnYmKhXR6yEwMBAVK1bEpk2bGIQTmQEORyGLFB8fj1KlSmkNwAHAw8PDYHkdPHgQT548Qa9evdCrVy9kZGRg7969xdpGSEgIAODWrVs6l9m4cSN8fHywf/9+jXmCIKBly5Zqwf2RI0fw0UcfoW3btqhbty4CAwMxfPjwIo/5HDJkCNq0aaORnpiYCB8fHyxdulQtXRRFbNy4Eb1790a9evXQoEEDDBkyRGPojy45OTmIjIxE8+bNYWNjozZP2zje59M2bNiAjh07ok6dOujevTsOHjwIALh8+TLef/99NGzYEE2aNMGMGTOgVCq17uft27cxZswYNGrUCA0bNsS4ceNw+/ZttWUFQcBPP/2EQYMGITg4GAEBAWjVqhWmT5+Op0+fat2viIgIDBkyBIGBgahXrx46duyIGTNmIDs7G9u2bcPQoUMBAJ9//rlqmNKQIUNeWl+JiYmYMmUKmjdvjoCAALRr1w4LFixAZmam2nJLly6Fj48Pbty4gQULFqBly5YICAjAW2+9hb///vul+QAF47CPHTuGZcuWoXXr1qhbty769u2L2NhYAMDJkycxYMAA1K9fHyEhIRpnM/JFRkaif//+qF+/Pho0aID+/fsjMjJS67KbN29Gp06dEBAQgPbt22PdunU6h0qkpqZi7ty5aN++PQICAtC0aVNMmjRJ4z0srqLW84uuq/Dx8cHUqVMB5LXbtm3bAgCWLVumes/zP2vPf77+/PNPdO/eHXXq1EGrVq2wdOlS5OTkqG27qJ/TorQ1mUyGkJAQ/PPPP0hPTy9JdRGRAbEnnCxSlSpVcPPmTezbtw8dOnQo0jq5ubk6x3xnZ2frXG/r1q2oVKkSAgMDIZPJ4O/vj9DQUPTt27fI5Y2PjwcAuLu761yma9eumDVrFsLCwlRf4vmOHTuGBw8eYPjw4aq07du349mzZ+jZsyc8PT3x4MEDbNmyBcOGDcMvv/zywiEzJTFlyhTs3r0bHTt2RO/evZGdnY1du3Zh+PDhWLp0qUaZC7tw4QIyMjJQt27dYuW7YcMGpKSkoG/fvrC1tcWvv/6K8ePHY/HixZg2bRq6deuGdu3a4ejRo/j1119RunRpjB07Vm0bGRkZGDJkCOrWrYtJkyYhISEBGzduxJkzZ7B9+3bVjzalUonVq1ejQ4cOaNu2LRwcHHDu3DmEhobi9OnTGsOJFi5ciOXLl6NmzZoYNmwYPDw8cOvWLezbtw8TJ05EUFAQRo8ejeXLl+Odd95Bo0aNAABly5Z94T7fuXMHffv2RWpqKgYOHIiqVavi5MmTWLFiBU6fPo1169ZpDN2ZOnUqrK2tMXz4cCiVSqxfvx7jxo1DeHg4KlWqVKS6njdvHgRBwNChQ6FUKrFmzRoMHz4cc+bMwZdffol+/fqhe/fu2Lt3L5YsWYJKlSqp/TDcsGEDvvvuO1SvXl31Hmzfvh3jxo3Dd999h3feeUe17Lp16zBr1iz4+vpi0qRJyMzMxJo1a1CmTBmNcqWmpqJ///64e/cu+vTpg1q1auHRo0fYuHEj+vbti9DQUFSsWLFI+6hvPb9MjRo18Pnnn2PWrFlo37492rdvDwBwcnJSW+7AgQO4ffs2Bg0ahLJly+LAgQNYtmwZ7t69i1mzZhV7X4ra1ho0aIA//vgDp06dQsuWLYudDxEZkEhkgU6fPi3Wrl1b9Pb2Fjt06CBOnTpV3LBhg3jt2jWty7du3Vr09vZ+6evJkydq692/f1/08/MTlyxZokpbt26d6O3trTUvb29vcfjw4eKTJ0/EJ0+eiDdv3hTXrl0r1q5dW2zUqJH4+PHjF+7XhAkTxICAADE5OVkt/ZNPPhH9/f3V1k9PT9dY/9GjR2Ljxo3FESNGqKV/9tlnore3t1ra4MGDxdatW2ts4/bt26K3t7faPu/bt0/09vYWN23apLasUqkUe/XqJbZu3VoUBOGF+7Z161bR29tbjIyM1Jh3/Phx0dvbWwwNDdVICwkJEVNSUlTpcXFxore3t+jj4yNGRESobadXr15icHCwxn56e3uLM2bMUEvP36evvvpKlSYIgpiZmalRvs2bN4ve3t7i7t27VWlnzpwRvb29xSFDhogKhUJteUEQVPWhbd9eZtKkSaK3t7d46NAhtfTvv/9e9Pb2Fjdv3qxKW7Jkiejt7S2OHDlS7T3IL9+8efNeml9oaKjo7e0t9uzZU8zKylKlR0ZGit7e3qK/v7949uxZVXpWVpYYHBws9uvXT5WWnJws1q9fX2zXrp2YmpqqSk9NTRXbtm0r1q9fX3z27JkoiqL47NkzsV69emLnzp3FjIwM1bL37t0T69evL3p7e4vHjx9Xpf/vf/8T69SpI8bFxamVOzExUWzQoIH42WefqdKKU9/FqWdtn6F83t7eamXQ9hkqPM/X11c8f/68Kl0QBHHs2LGit7e3+O+//6rSi/M5Lcq+R0dHi97e3uLq1at1LkNExsHhKGSRGjRogNDQUPTq1QupqanYtm0bvv32W3Tp0gWDBg3Seoq6YsWKWLt2rdZX/nCRwrZv3w5BENCzZ09VWvfu3WFjY4OtW7dqXefIkSNo1qwZmjVrho4dO2LWrFmoUaOGzl6+5/Xq1QvZ2dnYs2ePKi09PR2RkZFo0aKF2vqOjo5qyzx9+hRyuRz16tXD2bNnX5hPce3cuRNOTk5o164dkpKSVK+UlBS0adMGd+7cUfX265J/FsLNza1Yeffu3RsuLi6qaV9fXzg7O6NcuXIaZ0EaNmyIR48eaT3VPnLkSLXp9u3bo1q1amrDf2QyGezt7QHknTlJSUlBUlKS6iLf5+t1586dAIDJkydrjGeXyWSQyWTF2s98giDgwIED8Pf31xg7P2rUKMjlcq3DO4YOHaqWZ926deHo6IiEhIQi5z1gwAC1nv78syl169ZFnTp1VOm2traoU6eO2nt+9OhR1RmH56+XcHZ2xpAhQ5CRkYGoqCgAeZ+RzMxMDBo0CA4ODqplPT090b17d7UyiaKIXbt2ISgoCOXKlVNrfw4ODqhfvz6OHDlS5H3MV9J6NpTmzZujdu3aqmmZTIYRI0YAAP766y/J8s0/G/fkyRPJ8iCiouFwFLJYPj4++P777wHknVaOjo7Gli1bEBMTg7Fjx2oMHXB0dETz5s21bis/oHqeKIoIDQ2Fj48PBEFQC2YaNGiAnTt3YvLkyRqnq+vVq4ePPvoIQF6wUqFCBVSoUKFI+5QfaIeFhWHAgAEAgH379iEjI0PttD+QN7584cKFOHLkCFJSUtTmlTQA1OX69etIT0/XWX9A3pd6tWrVdM4vaZm0DaVwc3ODp6en1nQASE5OVjv97+rqqvU6gRo1aiAyMhIZGRmqHzV79uzB2rVrERcXpzG+/NmzZ6r/ExISIJPJdF6XUFJJSUnIyMhAzZo1NeaVKlUKHh4eWn9kVq5cWSPN3d1d51h2bQpvI78+db0Hz992MzExEQBQq1YtjWXz0/LLnb9s9erVNZatUaOG2nRSUhKSk5NVP261kcuL359U0no2lML7CUBVFinzFf8bc2/oYwQRFR+DcHolVKxYERUrVkSPHj0wcOBAnD59GmfPntVrXPTJkydVF1LqGnd+6NAhtGvXTi3N3d39hcHqi1hbW6Nbt25Yv349EhISULVqVezYsQNubm5qY67T09MxaNAgZGZm4t1334W3tzecnJwgl8uxYsWKIl8sqU1ubq5GmiiKKF26NObPn69zPW3B1/NKly4NAMW+X7qVlVWx0gGU+D7I+/btw8cff4y6deviiy++QPny5WFnZ4fc3FyMGDFCY7v69HgbWkkC0aJu40V1LbX8Om/evDk++OADk5VD1/tc+EJKY9H2OS2K/M9f/ueRiEyHQTi9UmQyGerVq4fTp0/j4cOHem0rvyd99uzZWoOT6dOnY+vWrRpBuL569eqF9evXY8eOHejXrx9OnjyJfv36qfXqHzt2DA8fPsTMmTPRp08ftfUXLVpUpHxKlSqFCxcuaKRr64WrWrUq4uPjUa9ePY0LzIoqP0gvzvAIQ0lJScGjR480esOvX7+OMmXKqHrBw8LCYGdnh19++UVtmMT169c1tunl5YXDhw/j0qVLL7zYtLhBeunSpeHk5IRr165pzHv27BkePXpklvcbz+9Fv3r1qkaPdf6+5C+T37N+48YNjWUL13Xp0qXh6uqKtLS0Ev+41aa49fz8WZZSpUqp0rV9XorynmtrU4XrCSje57Qo+eZ3LLzsRzMRSY9jwskiHT16VGsPlEKhUD0OXdvp3qJKTU1FREQEgoOD0aVLF3Tq1Enj1aZNGxw+fFjvYL8wPz8/+Pj4YOfOnQgLC4MgCOjVq5faMvk9k4V7Zo8cOYIzZ84UKR8vLy+kp6erjXMWBAHr1q3TWLZnz54QBAELFizQuq3Hjx+/ND9/f384OzsXuXyGtnLlSrXpv/76Czdv3lT7EWVlZQWZTAZBEFRpoijip59+0the/tjlBQsWaL27Tv57kx/gPz+U5UXkcjlat26Nixcv4vDhwxr7IAiCwX/4GUJwcDAcHR3x22+/IS0tTZWelpaG3377DY6OjqqnpAYHB8Pe3h4bNmxQuxXg/fv3sWvXLrXtyuVydO/eHWfPnkV4eLjWvEsyvrm49ezl5QUAqnHt+dauXaux7aK851FRUWrBtSiK+PnnnwFAI9+ifk6Lkm9sbCysra3RsGFDncsQkXGwJ5wsUv5j4Nu0aQNvb2/Y29urvsDj4+PRs2dPnff0LYo///wTCoUCHTt21LlMhw4dsG3bNuzYsUPjoj999erVC99//z1WrVoFLy8v1K9fX21+o0aN4OHhgdmzZ+POnTvw9PREXFwcwsLC4O3tjStXrrw0j379+mHt2rUYN24chg4dChsbG0RERGg9zd2pUyf07t0bv/32Gy5cuIDWrVvD3d0d9+/fR2xsLBISErTe3/x5VlZW6NChAyIjI5GdnW3UJ4e6u7vjr7/+wsOHD9G4cWPVLQrLli2L8ePHq5br2LEjIiIi8O6776Jnz56qe5sXvmc0kHex4gcffIBVq1ahd+/e6Ny5Mzw8PJCYmIiIiAhs2bIFrq6uqFmzJpycnLBx40bY29vD1dUVpUuX1jm+GQAmTZqEqKgojBs3DgMHDkSVKlUQExODPXv2ICgoSONHmTlwdXXFJ598gu+++w79+vVTlXH79u1ISEjAd999p7rA1s3NDR9++CFmz56N/v37o2fPnsjMzMSmTZvg5eWFixcvqm37448/xunTp/HRRx+hc+fOqFevHmxsbHD37l0cPnwYtWvXVl0fUhzFqedu3bph4cKF+Prrr3Hjxg2UKlUK//zzj9Yx9+7u7qhatSp2796NypUro2zZsnBwcFC737evry/effddDBo0CB4eHti/fz+ioqLQo0cPNGjQQLVccT6nL2troijiyJEjaNGiRYnPaBGR4TAIJ4s0depU7N+/H6dOnUJERARSU1Ph4uICb29vfPDBB+jdu7de29+6dSusra21PiQjX3BwMJycnBAaGmrwILx79+6YN28e0tLSVHdMeJ6rqyt+/vlnzJ07F7/99htycnIQEBCAVatWYevWrUUKwitXrowffvgBCxYswOLFi1GqVCn06NEDffr00fpUz1mzZqFJkybYvHkzVqxYAaVSCQ8PD/j7+2Py5MlF2q8BAwZg27ZtOHjw4At/4Biao6Mj1q9fj5kzZ2L+/PkQRREtWrTA1KlTUa5cOdVyXbt2RXp6OtatW4fZs2fDzc0NrVu3xuTJk7U+fvyTTz6Br68vfvvtN/z8888QRRGenp5o2bKl6i4r9vb2WLhwIRYtWoSZM2ciOzsbjRs3fmEQXrFiRWzevBlLlizBzp07kZqaijfeeAOjRo3CmDFjin3vamMZNGgQypUrh9WrV6se5uPr64sffvhBo/d++PDhcHR0xNq1azF//nyUL18ew4cPh4uLC7744gu1ZV1cXPD7779jzZo1CA8Px/79+2FlZQVPT080atSoWPfsf15x6tnZ2RkrV67ErFmzsGLFCjg6OqJDhw6YO3cugoKCNLY9b948zJw5EwsXLkRmZiYqVqyodjxp06YNqlWrhhUrVuDmzZsoU6YMxo4dq3GP++J8Tl/W1qKjo3Hnzh18/fXXJaovIjIsmVjSK5iIiErg/fffR2ZmJjZu3GiU/IYMGYI7d+7gwIEDRsmP6EUSExPRtm1bjB8/HhMmTDBq3uPGjcO9e/cQGhpqNhcUE73OOCaciIxq6tSpiI2NLdG9nYmoZC5evIj9+/dj6tSpDMCJzIR5ntMkoldWrVq1NMb8EpG0/P39cenSJVMXg4iew55wIiIiIiIj45hwIiIiIiIjY084EREREZGRMQgnIiIiIjIyBuFEREREREbGIJyIiIiIyMgYhBMRERERGRmDcCIiIiIiI2MQTkRERERkZAzCiYiIiIiMjEE4EREREZGR/T/gBgR6Dp4NRQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.05621256  0.05121078  0.04381478  0.05647308]\n",
            " [ 0.01641    -0.11045878 -0.03386583 -0.09999849]\n",
            " [ 0.01575747  0.06252643  0.01833241  0.07230096]\n",
            " [ 0.01847075 -0.00669259 -0.02402451  0.02928081]\n",
            " [-0.03866266  0.04821499 -0.03933304 -0.01729678]\n",
            " [ 0.00249688 -0.04054043  0.01430706 -0.04980212]\n",
            " [-0.00357742  0.04477839 -0.01272988  0.08200837]\n",
            " [-0.03970475  0.02493794  0.00748855 -0.01150472]\n",
            " [-0.00368778 -0.00205248  0.02038608 -0.02685281]\n",
            " [ 0.04911785  0.04369219  0.02974203  0.03511627]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb8e6d5dd0>\n",
            "Shape values [0.04381478 0.05621256 0.06252643 0.08200837]\n",
            "Shap values final [0.00728329 0.01156164 0.00241177 0.00697246]\n",
            "Coefficients: \n",
            " [[-0.13227273  0.00227273 -0.03977273 -0.00977273]]\n",
            "Mean squared error: 0.01\n",
            "Coefficient of determination: 0.75\n",
            "Evaluating classroom: Class 3 - STI\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb8e5c4790>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.20049884672133783\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bfccc6b7f5a64cc785809d4b699e0687"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.03941044 -0.04959994  0.00673146  0.00809097]\n",
            " [ 0.02330528 -0.02576522 -0.00295862 -0.02324241]\n",
            " [ 0.04155235 -0.02094338 -0.00330207  0.02107984]\n",
            " [ 0.0282522   0.0126126   0.01000891 -0.02566119]\n",
            " [ 0.03785282 -0.03829279  0.00129011  0.02127253]\n",
            " [ 0.01884826  0.00833502 -0.01111348  0.01993103]\n",
            " [-0.04210067 -0.05134135 -0.00425047  0.00560053]\n",
            " [-0.03213938  0.00619294 -0.00859641 -0.0316691 ]\n",
            " [-0.02997098  0.01083621  0.01319406 -0.02528403]\n",
            " [ 0.03142991  0.00881695 -0.00643546 -0.01908745]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb98373270>\n",
            "Shape values [0.0126126  0.01319406 0.02127253 0.04155235]\n",
            "Shap values final [ 0.00376194 -0.0139149  -0.0005432  -0.00489693]\n",
            "Coefficients: \n",
            " [[-0.13852273  0.03102273 -0.02227273  0.01522727]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.91\n",
            "Evaluating classroom: Class 4 - STI\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb99569ab0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.7498570351744328\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a9428a9cc0614611aae5b2a769057e6c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.09311626  0.08780894  0.01575207  0.01416793]\n",
            " [ 0.08601066  0.15737446 -0.01255307  0.01366371]\n",
            " [ 0.07228145  0.1855882  -0.02983397 -0.01090159]\n",
            " [ 0.05282663 -0.05839867  0.04088181 -0.00976177]\n",
            " [ 0.09541318  0.13454711  0.04965127  0.01411818]\n",
            " [ 0.01599625 -0.08266771 -0.05195961 -0.03060303]\n",
            " [-0.06677226  0.10963925 -0.01425745  0.00206642]\n",
            " [-0.03567212 -0.04207113 -0.01605074  0.00936459]\n",
            " [-0.04941485 -0.03177137  0.02259034 -0.00280314]\n",
            " [ 0.04229615 -0.06917922 -0.02203247  0.0356645 ]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb995bc1b0>\n",
            "Shape values [0.0356645  0.04965127 0.09541318 0.1855882 ]\n",
            "Shap values final [ 0.01198488  0.03908699 -0.00178118  0.00349758]\n",
            "Coefficients: \n",
            " [[-0.10693182  0.04943182 -0.01693182  0.01431818]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.77\n",
            "Evaluating classroom: Class 5 - STI\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbba1331630>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 0.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c8e4354c96f14523ae20d9a9202f29d3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]\n",
            " [0. 0. 0. 0.]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbb997d99b0>\n",
            "Shape values [0. 0. 0. 0.]\n",
            "Shap values final [0. 0. 0. 0.]\n",
            "Coefficients: \n",
            " [[-0.12545455  0.03045455 -0.01795455  0.00204545]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.93\n",
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "``build_fn`` will be renamed to ``model`` in a future release, at which point use of ``build_fn`` will raise an Error instead.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<function auto_sensitivy_analisys.<locals>.DL_regression_model at 0x7bbb8e5c4af0>\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
            "\n",
            "Please adapt your code to use either `displot` (a figure-level function with\n",
            "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "For a guide to updating your code to use the new functions, please see\n",
            "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Slope Coefficient: 1.0030122708971845\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/10 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8ac8104bb54a4ab4b441ee50b8ee4a7e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x310 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.14780343  0.04328401 -0.04385267 -0.01351816]\n",
            " [ 0.135219    0.07409899  0.01220728  0.01339818]\n",
            " [ 0.12120533  0.07541626  0.00057867 -0.01162148]\n",
            " [ 0.0984907  -0.03034507 -0.03560532 -0.00717451]\n",
            " [ 0.14661966  0.08013181 -0.00480588  0.00363614]\n",
            " [ 0.09318701 -0.02760578  0.00258045 -0.01277988]\n",
            " [-0.11948375  0.03637158  0.01526589 -0.00072002]\n",
            " [-0.10160685 -0.00990477  0.01045756  0.00108541]\n",
            " [-0.09636869 -0.01041838 -0.02837112  0.01443389]\n",
            " [ 0.10663421 -0.02663021  0.01660503  0.01453261]]\n",
            "Shape values <built-in method sort of numpy.ndarray object at 0x7bbba154dcb0>\n",
            "Shape values [0.01453261 0.01660503 0.08013181 0.14661966]\n",
            "Shap values final [ 0.02360932  0.02043984 -0.00549401  0.00012722]\n",
            "Coefficients: \n",
            " [[-0.12545455  0.03045455 -0.01795455  0.00204545]]\n",
            "Mean squared error: 0.00\n",
            "Coefficient of determination: 0.93\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# result"
      ],
      "metadata": {
        "id": "8KToJswA4bCH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df= pd.DataFrame(result)"
      ],
      "metadata": {
        "id": "33ALX-CMRYRH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Flatten the nested arrays\n",
        "labels = ['A', 'B', 'C', 'D']\n",
        "df_expanded = pd.concat([df[0], df[1].apply(pd.Series).rename(lambda x: f'Shape {labels[x]}', axis=1),\n",
        "                        df[2].apply(pd.Series).rename(lambda x: f'Perm {labels[x]}', axis=1),\n",
        "                        df[3].apply(pd.Series).rename(lambda x: f'RL {labels[x]}', axis=1)], axis=1)\n",
        "\n",
        "# Display the expanded DataFrame\n",
        "df_expanded= df_expanded.rename(columns={0: 'CLASSROOM'})\n",
        "df_expanded"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "2Eyb618DB-9F",
        "outputId": "88227036-c2b6-4b12-db2d-68fedb4e8ec3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       CLASSROOM   Shape A   Shape B   Shape C   Shape D    Perm A    Perm B  \\\n",
              "0  Class 1 - T30  1.289115  0.225569  0.070264  0.007288  0.001284 -0.017706   \n",
              "1  Class 2 - T30  0.081982 -0.003588 -0.007129 -0.070961 -0.001645 -0.001183   \n",
              "2  Class 3 - T30  1.030466  0.575690  0.278094 -0.001346  0.002745 -0.061399   \n",
              "3  Class 4 - T30  0.000979  0.000653 -0.000131 -0.000140 -0.000048 -0.000482   \n",
              "4  Class 5 - T30  1.469469  0.415499  0.131695 -0.010879 -0.006447 -0.111941   \n",
              "5  Class 1 - STI  2.274096  0.150453  0.103827 -0.011500  0.041443  0.011279   \n",
              "6  Class 2 - STI  0.061600  0.047049 -0.258349 -0.355131  0.007283  0.011562   \n",
              "7  Class 3 - STI  0.348614  0.056079 -0.035536 -0.038198  0.003762 -0.013915   \n",
              "8  Class 4 - STI  1.515051  0.467203  0.099275 -0.193029  0.011985  0.039087   \n",
              "9  Class 5 - STI  2.545768  0.208267  0.081034  0.009713  0.023609  0.020440   \n",
              "\n",
              "     Perm C    Perm D      RL A      RL B      RL C      RL D  \n",
              "0  0.006776  0.007428 -0.000426 -0.087855 -0.008395 -0.031832  \n",
              "1  0.005638  0.002277  0.010142 -0.161861  0.086548 -0.056264  \n",
              "2  0.016716  0.007828  0.006108 -0.175795  0.120795 -0.077642  \n",
              "3 -0.000579 -0.000338  0.015625 -0.294688  0.032500 -0.164688  \n",
              "4  0.017759  0.017324  0.002216 -0.311278  0.117528 -0.083097  \n",
              "5  0.005782  0.012179 -0.196250 -0.007500 -0.005000  0.005000  \n",
              "6  0.002412  0.006972 -0.132273  0.002273 -0.039773 -0.009773  \n",
              "7 -0.000543 -0.004897 -0.138523  0.031023 -0.022273  0.015227  \n",
              "8 -0.001781  0.003498 -0.106932  0.049432 -0.016932  0.014318  \n",
              "9 -0.005494  0.000127 -0.125455  0.030455 -0.017955  0.002045  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4715c270-90dd-49d4-a168-5f8bd5e463cf\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CLASSROOM</th>\n",
              "      <th>Shape A</th>\n",
              "      <th>Shape B</th>\n",
              "      <th>Shape C</th>\n",
              "      <th>Shape D</th>\n",
              "      <th>Perm A</th>\n",
              "      <th>Perm B</th>\n",
              "      <th>Perm C</th>\n",
              "      <th>Perm D</th>\n",
              "      <th>RL A</th>\n",
              "      <th>RL B</th>\n",
              "      <th>RL C</th>\n",
              "      <th>RL D</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Class 1 - T30</td>\n",
              "      <td>1.289115</td>\n",
              "      <td>0.225569</td>\n",
              "      <td>0.070264</td>\n",
              "      <td>0.007288</td>\n",
              "      <td>0.001284</td>\n",
              "      <td>-0.017706</td>\n",
              "      <td>0.006776</td>\n",
              "      <td>0.007428</td>\n",
              "      <td>-0.000426</td>\n",
              "      <td>-0.087855</td>\n",
              "      <td>-0.008395</td>\n",
              "      <td>-0.031832</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Class 2 - T30</td>\n",
              "      <td>0.081982</td>\n",
              "      <td>-0.003588</td>\n",
              "      <td>-0.007129</td>\n",
              "      <td>-0.070961</td>\n",
              "      <td>-0.001645</td>\n",
              "      <td>-0.001183</td>\n",
              "      <td>0.005638</td>\n",
              "      <td>0.002277</td>\n",
              "      <td>0.010142</td>\n",
              "      <td>-0.161861</td>\n",
              "      <td>0.086548</td>\n",
              "      <td>-0.056264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Class 3 - T30</td>\n",
              "      <td>1.030466</td>\n",
              "      <td>0.575690</td>\n",
              "      <td>0.278094</td>\n",
              "      <td>-0.001346</td>\n",
              "      <td>0.002745</td>\n",
              "      <td>-0.061399</td>\n",
              "      <td>0.016716</td>\n",
              "      <td>0.007828</td>\n",
              "      <td>0.006108</td>\n",
              "      <td>-0.175795</td>\n",
              "      <td>0.120795</td>\n",
              "      <td>-0.077642</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Class 4 - T30</td>\n",
              "      <td>0.000979</td>\n",
              "      <td>0.000653</td>\n",
              "      <td>-0.000131</td>\n",
              "      <td>-0.000140</td>\n",
              "      <td>-0.000048</td>\n",
              "      <td>-0.000482</td>\n",
              "      <td>-0.000579</td>\n",
              "      <td>-0.000338</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>-0.294688</td>\n",
              "      <td>0.032500</td>\n",
              "      <td>-0.164688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Class 5 - T30</td>\n",
              "      <td>1.469469</td>\n",
              "      <td>0.415499</td>\n",
              "      <td>0.131695</td>\n",
              "      <td>-0.010879</td>\n",
              "      <td>-0.006447</td>\n",
              "      <td>-0.111941</td>\n",
              "      <td>0.017759</td>\n",
              "      <td>0.017324</td>\n",
              "      <td>0.002216</td>\n",
              "      <td>-0.311278</td>\n",
              "      <td>0.117528</td>\n",
              "      <td>-0.083097</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Class 1 - STI</td>\n",
              "      <td>2.274096</td>\n",
              "      <td>0.150453</td>\n",
              "      <td>0.103827</td>\n",
              "      <td>-0.011500</td>\n",
              "      <td>0.041443</td>\n",
              "      <td>0.011279</td>\n",
              "      <td>0.005782</td>\n",
              "      <td>0.012179</td>\n",
              "      <td>-0.196250</td>\n",
              "      <td>-0.007500</td>\n",
              "      <td>-0.005000</td>\n",
              "      <td>0.005000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Class 2 - STI</td>\n",
              "      <td>0.061600</td>\n",
              "      <td>0.047049</td>\n",
              "      <td>-0.258349</td>\n",
              "      <td>-0.355131</td>\n",
              "      <td>0.007283</td>\n",
              "      <td>0.011562</td>\n",
              "      <td>0.002412</td>\n",
              "      <td>0.006972</td>\n",
              "      <td>-0.132273</td>\n",
              "      <td>0.002273</td>\n",
              "      <td>-0.039773</td>\n",
              "      <td>-0.009773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Class 3 - STI</td>\n",
              "      <td>0.348614</td>\n",
              "      <td>0.056079</td>\n",
              "      <td>-0.035536</td>\n",
              "      <td>-0.038198</td>\n",
              "      <td>0.003762</td>\n",
              "      <td>-0.013915</td>\n",
              "      <td>-0.000543</td>\n",
              "      <td>-0.004897</td>\n",
              "      <td>-0.138523</td>\n",
              "      <td>0.031023</td>\n",
              "      <td>-0.022273</td>\n",
              "      <td>0.015227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Class 4 - STI</td>\n",
              "      <td>1.515051</td>\n",
              "      <td>0.467203</td>\n",
              "      <td>0.099275</td>\n",
              "      <td>-0.193029</td>\n",
              "      <td>0.011985</td>\n",
              "      <td>0.039087</td>\n",
              "      <td>-0.001781</td>\n",
              "      <td>0.003498</td>\n",
              "      <td>-0.106932</td>\n",
              "      <td>0.049432</td>\n",
              "      <td>-0.016932</td>\n",
              "      <td>0.014318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Class 5 - STI</td>\n",
              "      <td>2.545768</td>\n",
              "      <td>0.208267</td>\n",
              "      <td>0.081034</td>\n",
              "      <td>0.009713</td>\n",
              "      <td>0.023609</td>\n",
              "      <td>0.020440</td>\n",
              "      <td>-0.005494</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>-0.125455</td>\n",
              "      <td>0.030455</td>\n",
              "      <td>-0.017955</td>\n",
              "      <td>0.002045</td>\n",
              "    </tr>\n",
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          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Filter T30 and STI classrooms\n",
        "df = df_expanded\n",
        "df_t30 = df[df['CLASSROOM'].str.contains('T30')]\n",
        "df_sti = df[df['CLASSROOM'].str.contains('STI')]\n",
        "\n",
        "# Select T30 and STI parameter columns for each method\n",
        "shape_columns = ['Shape A', 'Shape B', 'Shape C', 'Shape D']\n",
        "perm_columns = ['Perm A', 'Perm B', 'Perm C', 'Perm D']\n",
        "rl_columns = ['RL A', 'RL B', 'RL C', 'RL D']\n",
        "\n",
        "# Extract T30 and STI parameter values for each method\n",
        "shape_t30 = df_t30.loc[:, ['CLASSROOM'] + shape_columns]\n",
        "perm_t30 = df_t30.loc[:, ['CLASSROOM'] + perm_columns]\n",
        "rl_t30 = df_t30.loc[:, ['CLASSROOM'] + rl_columns]\n",
        "\n",
        "shape_sti = df_sti.loc[:, ['CLASSROOM'] + shape_columns]\n",
        "perm_sti = df_sti.loc[:, ['CLASSROOM'] + perm_columns]\n",
        "rl_sti = df_sti.loc[:, ['CLASSROOM'] + rl_columns]\n",
        "\n",
        "# Set up the figure and axis with subplots\n",
        "fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(15, 10))\n",
        "\n",
        "# Plot bar plots for Shape, Perm, RL\n",
        "shape_t30.set_index('CLASSROOM').plot(kind='bar', ax=axes[0, 0], rot=0, title='Shape - T30')\n",
        "perm_t30.set_index('CLASSROOM').plot(kind='bar', ax=axes[1, 0], rot=0, title='Perm - T30')\n",
        "rl_t30.set_index('CLASSROOM').plot(kind='bar', ax=axes[2, 0], rot=0, title='RL - T30')\n",
        "\n",
        "shape_sti.set_index('CLASSROOM').plot(kind='bar', ax=axes[0, 1], rot=0, title='Shape - STI')\n",
        "perm_sti.set_index('CLASSROOM').plot(kind='bar', ax=axes[1, 1], rot=0, title='Perm - STI')\n",
        "rl_sti.set_index('CLASSROOM').plot(kind='bar', ax=axes[2, 1], rot=0, title='RL - STI')\n",
        "\n",
        "# Adjust layout\n",
        "plt.tight_layout()\n",
        "\n",
        "# Show the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 867
        },
        "id": "lk7cQ6zWtIHd",
        "outputId": "44280c2e-ee98-4caf-ebc3-d3d448ba882f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1000 with 6 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract columns for each group\n",
        "shape_columns = ['Shape A', 'Shape B', 'Shape C', 'Shape D']\n",
        "perm_columns = ['Perm A', 'Perm B', 'Perm C', 'Perm D']\n",
        "rl_columns = ['RL A', 'RL B', 'RL C', 'RL D']\n",
        "\n",
        "# Create new DataFrames for each group\n",
        "df_shape = df_expanded[shape_columns].apply(zscore, axis=1)\n",
        "df_perm = df_expanded[perm_columns].apply(zscore, axis=1)\n",
        "df_rl = df_expanded[rl_columns].apply(zscore, axis=1)\n",
        "\n",
        "# Rename the columns with the respective group and z-score\n",
        "df_shape.columns = [f'Shape_{i}_zscore' for i in range(len(df_shape.columns))]\n",
        "df_perm.columns = [f'Perm_{i}_zscore' for i in range(len(df_perm.columns))]\n",
        "df_rl.columns = [f'RL_{i}_zscore' for i in range(len(df_rl.columns))]\n",
        "\n",
        "# Concatenate the DataFrames\n",
        "df_zscores = pd.concat([df_shape, df_perm, df_rl], axis=1)\n",
        "\n",
        "# Display the new DataFrame with z-scores\n",
        "df_zscores"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "id": "Dd8m9yOhHZZY",
        "outputId": "29a70cc1-b13c-4e41-e52b-a123426aa5f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Shape_0_zscore  Shape_1_zscore  Shape_2_zscore  Shape_3_zscore  \\\n",
              "0        1.711762       -0.331362       -0.629710       -0.750690   \n",
              "1        1.506721       -0.067401       -0.132537       -1.306783   \n",
              "2        1.464548        0.274637       -0.504018       -1.235167   \n",
              "3        1.305070        0.638569       -0.962896       -0.980742   \n",
              "4        1.670217       -0.148293       -0.637964       -0.883960   \n",
              "5        1.728723       -0.503171       -0.552173       -0.673379   \n",
              "6        1.021703        0.942544       -0.718871       -1.245375   \n",
              "7        1.681411       -0.168607       -0.747986       -0.764818   \n",
              "8        1.614484       -0.007620       -0.577184       -1.029680   \n",
              "9        1.728159       -0.473757       -0.593610       -0.660793   \n",
              "\n",
              "   Perm_0_zscore  Perm_1_zscore  Perm_2_zscore  Perm_3_zscore  RL_0_zscore  \\\n",
              "0       0.180519      -1.683853       0.719692       0.783642     0.927395   \n",
              "1      -0.991530      -0.834599       1.484440       0.341689     0.444075   \n",
              "2       0.364433      -1.709273       0.816079       0.528762     0.346127   \n",
              "3       1.565016      -0.601929      -1.083473       0.120386     0.876825   \n",
              "4       0.268726      -1.702788       0.721099       0.712963     0.451045   \n",
              "5       1.705133      -0.458487      -0.852723      -0.393923    -1.729366   \n",
              "6       0.069805       1.391261      -1.434864      -0.026202    -1.657416   \n",
              "7       1.170673      -1.530794       0.512740      -0.152620    -1.656659   \n",
              "8      -0.077044       1.645517      -0.951991      -0.616482    -1.583941   \n",
              "9       1.109515       0.857226      -1.207094      -0.759647    -1.656771   \n",
              "\n",
              "   RL_1_zscore  RL_2_zscore  RL_3_zscore  \n",
              "0    -1.630291     0.694274     0.008623  \n",
              "1    -1.441873     1.281842    -0.284045  \n",
              "2    -1.322107     1.397924    -0.421944  \n",
              "3    -1.420503     1.001755    -0.458078  \n",
              "4    -1.544059     1.184904    -0.091890  \n",
              "5     0.516950     0.546703     0.665713  \n",
              "6     0.894444     0.096988     0.665984  \n",
              "7     0.899427     0.095939     0.661293  \n",
              "8     1.110962    -0.032805     0.505784  \n",
              "9     0.986357     0.165677     0.504737  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9299c734-07c3-45f4-80ca-dee044d006b0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Shape_0_zscore</th>\n",
              "      <th>Shape_1_zscore</th>\n",
              "      <th>Shape_2_zscore</th>\n",
              "      <th>Shape_3_zscore</th>\n",
              "      <th>Perm_0_zscore</th>\n",
              "      <th>Perm_1_zscore</th>\n",
              "      <th>Perm_2_zscore</th>\n",
              "      <th>Perm_3_zscore</th>\n",
              "      <th>RL_0_zscore</th>\n",
              "      <th>RL_1_zscore</th>\n",
              "      <th>RL_2_zscore</th>\n",
              "      <th>RL_3_zscore</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.711762</td>\n",
              "      <td>-0.331362</td>\n",
              "      <td>-0.629710</td>\n",
              "      <td>-0.750690</td>\n",
              "      <td>0.180519</td>\n",
              "      <td>-1.683853</td>\n",
              "      <td>0.719692</td>\n",
              "      <td>0.783642</td>\n",
              "      <td>0.927395</td>\n",
              "      <td>-1.630291</td>\n",
              "      <td>0.694274</td>\n",
              "      <td>0.008623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.506721</td>\n",
              "      <td>-0.067401</td>\n",
              "      <td>-0.132537</td>\n",
              "      <td>-1.306783</td>\n",
              "      <td>-0.991530</td>\n",
              "      <td>-0.834599</td>\n",
              "      <td>1.484440</td>\n",
              "      <td>0.341689</td>\n",
              "      <td>0.444075</td>\n",
              "      <td>-1.441873</td>\n",
              "      <td>1.281842</td>\n",
              "      <td>-0.284045</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.464548</td>\n",
              "      <td>0.274637</td>\n",
              "      <td>-0.504018</td>\n",
              "      <td>-1.235167</td>\n",
              "      <td>0.364433</td>\n",
              "      <td>-1.709273</td>\n",
              "      <td>0.816079</td>\n",
              "      <td>0.528762</td>\n",
              "      <td>0.346127</td>\n",
              "      <td>-1.322107</td>\n",
              "      <td>1.397924</td>\n",
              "      <td>-0.421944</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.305070</td>\n",
              "      <td>0.638569</td>\n",
              "      <td>-0.962896</td>\n",
              "      <td>-0.980742</td>\n",
              "      <td>1.565016</td>\n",
              "      <td>-0.601929</td>\n",
              "      <td>-1.083473</td>\n",
              "      <td>0.120386</td>\n",
              "      <td>0.876825</td>\n",
              "      <td>-1.420503</td>\n",
              "      <td>1.001755</td>\n",
              "      <td>-0.458078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.670217</td>\n",
              "      <td>-0.148293</td>\n",
              "      <td>-0.637964</td>\n",
              "      <td>-0.883960</td>\n",
              "      <td>0.268726</td>\n",
              "      <td>-1.702788</td>\n",
              "      <td>0.721099</td>\n",
              "      <td>0.712963</td>\n",
              "      <td>0.451045</td>\n",
              "      <td>-1.544059</td>\n",
              "      <td>1.184904</td>\n",
              "      <td>-0.091890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1.728723</td>\n",
              "      <td>-0.503171</td>\n",
              "      <td>-0.552173</td>\n",
              "      <td>-0.673379</td>\n",
              "      <td>1.705133</td>\n",
              "      <td>-0.458487</td>\n",
              "      <td>-0.852723</td>\n",
              "      <td>-0.393923</td>\n",
              "      <td>-1.729366</td>\n",
              "      <td>0.516950</td>\n",
              "      <td>0.546703</td>\n",
              "      <td>0.665713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1.021703</td>\n",
              "      <td>0.942544</td>\n",
              "      <td>-0.718871</td>\n",
              "      <td>-1.245375</td>\n",
              "      <td>0.069805</td>\n",
              "      <td>1.391261</td>\n",
              "      <td>-1.434864</td>\n",
              "      <td>-0.026202</td>\n",
              "      <td>-1.657416</td>\n",
              "      <td>0.894444</td>\n",
              "      <td>0.096988</td>\n",
              "      <td>0.665984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1.681411</td>\n",
              "      <td>-0.168607</td>\n",
              "      <td>-0.747986</td>\n",
              "      <td>-0.764818</td>\n",
              "      <td>1.170673</td>\n",
              "      <td>-1.530794</td>\n",
              "      <td>0.512740</td>\n",
              "      <td>-0.152620</td>\n",
              "      <td>-1.656659</td>\n",
              "      <td>0.899427</td>\n",
              "      <td>0.095939</td>\n",
              "      <td>0.661293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.614484</td>\n",
              "      <td>-0.007620</td>\n",
              "      <td>-0.577184</td>\n",
              "      <td>-1.029680</td>\n",
              "      <td>-0.077044</td>\n",
              "      <td>1.645517</td>\n",
              "      <td>-0.951991</td>\n",
              "      <td>-0.616482</td>\n",
              "      <td>-1.583941</td>\n",
              "      <td>1.110962</td>\n",
              "      <td>-0.032805</td>\n",
              "      <td>0.505784</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.728159</td>\n",
              "      <td>-0.473757</td>\n",
              "      <td>-0.593610</td>\n",
              "      <td>-0.660793</td>\n",
              "      <td>1.109515</td>\n",
              "      <td>0.857226</td>\n",
              "      <td>-1.207094</td>\n",
              "      <td>-0.759647</td>\n",
              "      <td>-1.656771</td>\n",
              "      <td>0.986357</td>\n",
              "      <td>0.165677</td>\n",
              "      <td>0.504737</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "def perform_anova_and_decision(dataframe, group_columns, significance_level=0.05):\n",
        "    \"\"\"\n",
        "    Perform one-way ANOVA on the specified groups in the dataframe.\n",
        "\n",
        "    Parameters:\n",
        "    - dataframe: pandas DataFrame\n",
        "        The DataFrame containing the z-scores for different groups.\n",
        "    - group_columns: list\n",
        "        List of column names representing the groups.\n",
        "    - significance_level: float, optional (default=0.05)\n",
        "        The significance level for the hypothesis test.\n",
        "\n",
        "    Returns:\n",
        "    - result: str\n",
        "        A string indicating whether to accept or reject the null hypothesis.\n",
        "    \"\"\"\n",
        "    # Perform ANOVA for the specified groups\n",
        "    anova_result = f_oneway(*[dataframe[col] for col in group_columns])\n",
        "\n",
        "    # Check the p-value against the significance level\n",
        "    p_value = anova_result.pvalue\n",
        "\n",
        "    if p_value < significance_level:\n",
        "        return f\"Reject the null hypothesis. (p-value: {p_value:.4f})\"\n",
        "    else:\n",
        "        return f\"Accept the null hypothesis. (p-value: {p_value:.4f})\"\n",
        "\n",
        "# Example usage:\n",
        "# Assuming df_zscores has been created in the previous code\n",
        "shape_columns = [f'Shape_{i}_zscore' for i in range(4)]\n",
        "perm_columns = [f'Perm_{i}_zscore' for i in range(4)]\n",
        "rl_columns = [f'RL_{i}_zscore' for i in range(4)]\n",
        "\n",
        "print(\"ANOVA Decision for Shape:\", perform_anova_and_decision(df_zscores, shape_columns))\n",
        "print(\"ANOVA Decision for Perm:\", perform_anova_and_decision(df_zscores, perm_columns))\n",
        "print(\"ANOVA Decision for RL:\", perform_anova_and_decision(df_zscores, rl_columns))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZChQF9NKKTwA",
        "outputId": "f9c09a25-55e1-4687-cc11-36cd08c2768b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ANOVA Decision for Shape: Reject the null hypothesis. (p-value: 0.0000)\n",
            "ANOVA Decision for Perm: Accept the null hypothesis. (p-value: 0.1650)\n",
            "ANOVA Decision for RL: Reject the null hypothesis. (p-value: 0.0418)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# In ANOVA, the null hypothesis is that the means of the groups are equal"
      ],
      "metadata": {
        "id": "zEfhTNvMerC0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the correlation matrix\n",
        "correlation_matrix = df_expanded.corr()\n",
        "\n",
        "# Create a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(correlation_matrix, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "plt.figure(figsize=(10, 8))\n",
        "\n",
        "# Create a heatmap using seaborn with the lower triangular mask\n",
        "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=.5, mask=mask)\n",
        "\n",
        "# Show the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "BFzN8be6e6co",
        "outputId": "ef12588c-ad85-4949-e05a-19094015d0f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip freeze"
      ],
      "metadata": {
        "id": "hD5ZrWyKs3NU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "90291231-c86c-4b7d-9066-d0cecc5c11b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "absl-py==1.4.0\n",
            "aiohttp==3.9.1\n",
            "aiosignal==1.3.1\n",
            "alabaster==0.7.13\n",
            "albumentations==1.3.1\n",
            "altair==4.2.2\n",
            "anyio==3.7.1\n",
            "appdirs==1.4.4\n",
            "argon2-cffi==23.1.0\n",
            "argon2-cffi-bindings==21.2.0\n",
            "array-record==0.5.0\n",
            "arviz==0.15.1\n",
            "astropy==5.3.4\n",
            "astunparse==1.6.3\n",
            "async-timeout==4.0.3\n",
            "atpublic==4.0\n",
            "attrs==23.1.0\n",
            "audioread==3.0.1\n",
            "autograd==1.6.2\n",
            "Babel==2.13.1\n",
            "backcall==0.2.0\n",
            "beautifulsoup4==4.11.2\n",
            "bidict==0.22.1\n",
            "bigframes==0.15.0\n",
            "bleach==6.1.0\n",
            "blinker==1.4\n",
            "blis==0.7.11\n",
            "blosc2==2.0.0\n",
            "bokeh==3.3.2\n",
            "bqplot==0.12.42\n",
            "branca==0.7.0\n",
            "build==1.0.3\n",
            "CacheControl==0.13.1\n",
            "cachetools==5.3.2\n",
            "catalogue==2.0.10\n",
            "certifi==2023.11.17\n",
            "cffi==1.16.0\n",
            "chardet==5.2.0\n",
            "charset-normalizer==3.3.2\n",
            "chex==0.1.7\n",
            "click==8.1.7\n",
            "click-plugins==1.1.1\n",
            "cligj==0.7.2\n",
            "cloudpickle==2.2.1\n",
            "cmake==3.27.9\n",
            "cmdstanpy==1.2.0\n",
            "colorcet==3.0.1\n",
            "colorlover==0.3.0\n",
            "colour==0.1.5\n",
            "community==1.0.0b1\n",
            "confection==0.1.4\n",
            "cons==0.4.6\n",
            "contextlib2==21.6.0\n",
            "contourpy==1.2.0\n",
            "cryptography==41.0.7\n",
            "cufflinks==0.17.3\n",
            "cupy-cuda11x==11.0.0\n",
            "cvxopt==1.3.2\n",
            "cvxpy==1.3.2\n",
            "cycler==0.12.1\n",
            "cymem==2.0.8\n",
            "Cython==3.0.6\n",
            "dask==2023.8.1\n",
            "datascience==0.17.6\n",
            "db-dtypes==1.1.1\n",
            "dbus-python==1.2.18\n",
            "debugpy==1.6.6\n",
            "decorator==4.4.2\n",
            "defusedxml==0.7.1\n",
            "diskcache==5.6.3\n",
            "distributed==2023.8.1\n",
            "distro==1.7.0\n",
            "dlib==19.24.2\n",
            "dm-tree==0.1.8\n",
            "docutils==0.18.1\n",
            "dopamine-rl==4.0.6\n",
            "duckdb==0.9.2\n",
            "earthengine-api==0.1.381\n",
            "easydict==1.11\n",
            "ecos==2.0.12\n",
            "editdistance==0.6.2\n",
            "eerepr==0.0.4\n",
            "eli5==0.13.0\n",
            "en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.6.0/en_core_web_sm-3.6.0-py3-none-any.whl#sha256=83276fc78a70045627144786b52e1f2728ad5e29e5e43916ec37ea9c26a11212\n",
            "entrypoints==0.4\n",
            "et-xmlfile==1.1.0\n",
            "etils==1.5.2\n",
            "etuples==0.3.9\n",
            "exceptiongroup==1.2.0\n",
            "fastai==2.7.13\n",
            "fastcore==1.5.29\n",
            "fastdownload==0.0.7\n",
            "fastjsonschema==2.19.0\n",
            "fastprogress==1.0.3\n",
            "fastrlock==0.8.2\n",
            "filelock==3.13.1\n",
            "fiona==1.9.5\n",
            "firebase-admin==5.3.0\n",
            "Flask==2.2.5\n",
            "flatbuffers==23.5.26\n",
            "flax==0.7.5\n",
            "folium==0.14.0\n",
            "fonttools==4.46.0\n",
            "frozendict==2.3.10\n",
            "frozenlist==1.4.0\n",
            "fsspec==2023.6.0\n",
            "future==0.18.3\n",
            "gast==0.5.4\n",
            "gcsfs==2023.6.0\n",
            "GDAL==3.4.3\n",
            "gdown==4.6.6\n",
            "geemap==0.29.6\n",
            "gensim==4.3.2\n",
            "geocoder==1.38.1\n",
            "geographiclib==2.0\n",
            "geopandas==0.13.2\n",
            "geopy==2.3.0\n",
            "gin-config==0.5.0\n",
            "glob2==0.7\n",
            "google==2.0.3\n",
            "google-ai-generativelanguage==0.3.3\n",
            "google-api-core==2.11.1\n",
            "google-api-python-client==2.84.0\n",
            "google-auth==2.17.3\n",
            "google-auth-httplib2==0.1.1\n",
            "google-auth-oauthlib==1.0.0\n",
            "google-cloud-aiplatform==1.36.4\n",
            "google-cloud-bigquery==3.12.0\n",
            "google-cloud-bigquery-connection==1.12.1\n",
            "google-cloud-bigquery-storage==2.23.0\n",
            "google-cloud-core==2.3.3\n",
            "google-cloud-datastore==2.15.2\n",
            "google-cloud-firestore==2.11.1\n",
            "google-cloud-functions==1.13.3\n",
            "google-cloud-iam==2.12.2\n",
            "google-cloud-language==2.9.1\n",
            "google-cloud-resource-manager==1.10.4\n",
            "google-cloud-storage==2.8.0\n",
            "google-cloud-translate==3.11.3\n",
            "google-colab @ file:///colabtools/dist/google-colab-1.0.0.tar.gz#sha256=7677e7445dd4d529d32195af3e563d0b365c5b1fa354d6677b1a5f6ecffab5d4\n",
            "google-crc32c==1.5.0\n",
            "google-generativeai==0.2.2\n",
            "google-pasta==0.2.0\n",
            "google-resumable-media==2.6.0\n",
            "googleapis-common-protos==1.61.0\n",
            "googledrivedownloader==0.4\n",
            "graphviz==0.20.1\n",
            "greenlet==3.0.1\n",
            "grpc-google-iam-v1==0.12.7\n",
            "grpcio==1.59.3\n",
            "grpcio-status==1.48.2\n",
            "gspread==3.4.2\n",
            "gspread-dataframe==3.3.1\n",
            "gym==0.25.2\n",
            "gym-notices==0.0.8\n",
            "h5netcdf==1.3.0\n",
            "h5py==3.9.0\n",
            "holidays==0.38\n",
            "holoviews==1.17.1\n",
            "html5lib==1.1\n",
            "httpimport==1.3.1\n",
            "httplib2==0.22.0\n",
            "huggingface-hub==0.19.4\n",
            "humanize==4.7.0\n",
            "hyperopt==0.2.7\n",
            "ibis-framework==6.2.0\n",
            "idna==3.6\n",
            "imageio==2.31.6\n",
            "imageio-ffmpeg==0.4.9\n",
            "imagesize==1.4.1\n",
            "imbalanced-learn==0.10.1\n",
            "imgaug==0.4.0\n",
            "importlib-metadata==7.0.0\n",
            "importlib-resources==6.1.1\n",
            "imutils==0.5.4\n",
            "inflect==7.0.0\n",
            "iniconfig==2.0.0\n",
            "install==1.3.5\n",
            "intel-openmp==2023.2.0\n",
            "ipyevents==2.0.2\n",
            "ipyfilechooser==0.6.0\n",
            "ipykernel==5.5.6\n",
            "ipyleaflet==0.18.0\n",
            "ipython==7.34.0\n",
            "ipython-genutils==0.2.0\n",
            "ipython-sql==0.5.0\n",
            "ipytree==0.2.2\n",
            "ipywidgets==7.7.1\n",
            "itsdangerous==2.1.2\n",
            "jax==0.4.20\n",
            "jaxlib @ https://storage.googleapis.com/jax-releases/cuda11/jaxlib-0.4.20+cuda11.cudnn86-cp310-cp310-manylinux2014_x86_64.whl#sha256=01be66238133f884bf5adf15cd7eaaf8445f9d4b056c5c64df28a997a6aff2fe\n",
            "jeepney==0.7.1\n",
            "jieba==0.42.1\n",
            "Jinja2==3.1.2\n",
            "joblib==1.3.2\n",
            "jsonpickle==3.0.2\n",
            "jsonschema==4.19.2\n",
            "jsonschema-specifications==2023.11.2\n",
            "jupyter-client==6.1.12\n",
            "jupyter-console==6.1.0\n",
            "jupyter-server==1.24.0\n",
            "jupyter_core==5.5.0\n",
            "jupyterlab-widgets==3.0.9\n",
            "jupyterlab_pygments==0.3.0\n",
            "kaggle==1.5.16\n",
            "keras==2.14.0\n",
            "keyring==23.5.0\n",
            "kiwisolver==1.4.5\n",
            "langcodes==3.3.0\n",
            "launchpadlib==1.10.16\n",
            "lazr.restfulclient==0.14.4\n",
            "lazr.uri==1.0.6\n",
            "lazy_loader==0.3\n",
            "libclang==16.0.6\n",
            "librosa==0.10.1\n",
            "lida==0.0.10\n",
            "lightgbm==4.1.0\n",
            "linkify-it-py==2.0.2\n",
            "llmx==0.0.15a0\n",
            "llvmlite==0.41.1\n",
            "locket==1.0.0\n",
            "logical-unification==0.4.6\n",
            "lxml==4.9.3\n",
            "malloy==2023.1067\n",
            "Markdown==3.5.1\n",
            "markdown-it-py==3.0.0\n",
            "MarkupSafe==2.1.3\n",
            "matplotlib==3.7.1\n",
            "matplotlib-inline==0.1.6\n",
            "matplotlib-venn==0.11.9\n",
            "mdit-py-plugins==0.4.0\n",
            "mdurl==0.1.2\n",
            "miniKanren==1.0.3\n",
            "missingno==0.5.2\n",
            "mistune==0.8.4\n",
            "mizani==0.9.3\n",
            "mkl==2023.2.0\n",
            "ml-dtypes==0.2.0\n",
            "mlxtend==0.22.0\n",
            "more-itertools==10.1.0\n",
            "moviepy==1.0.3\n",
            "mpmath==1.3.0\n",
            "msgpack==1.0.7\n",
            "multidict==6.0.4\n",
            "multipledispatch==1.0.0\n",
            "multitasking==0.0.11\n",
            "murmurhash==1.0.10\n",
            "music21==9.1.0\n",
            "natsort==8.4.0\n",
            "nbclassic==1.0.0\n",
            "nbclient==0.9.0\n",
            "nbconvert==6.5.4\n",
            "nbformat==5.9.2\n",
            "nest-asyncio==1.5.8\n",
            "networkx==3.2.1\n",
            "nibabel==4.0.2\n",
            "nltk==3.8.1\n",
            "notebook==6.5.5\n",
            "notebook_shim==0.2.3\n",
            "numba==0.58.1\n",
            "numexpr==2.8.7\n",
            "numpy==1.23.5\n",
            "oauth2client==4.1.3\n",
            "oauthlib==3.2.2\n",
            "opencv-contrib-python==4.8.0.76\n",
            "opencv-python==4.8.0.76\n",
            "opencv-python-headless==4.8.1.78\n",
            "openpyxl==3.1.2\n",
            "opt-einsum==3.3.0\n",
            "optax==0.1.7\n",
            "orbax-checkpoint==0.4.4\n",
            "osqp==0.6.2.post8\n",
            "packaging==23.2\n",
            "pandas==1.5.3\n",
            "pandas-datareader==0.10.0\n",
            "pandas-gbq==0.19.2\n",
            "pandas-stubs==1.5.3.230304\n",
            "pandocfilters==1.5.0\n",
            "panel==1.3.4\n",
            "param==2.0.1\n",
            "parso==0.8.3\n",
            "parsy==2.1\n",
            "partd==1.4.1\n",
            "pathlib==1.0.1\n",
            "pathy==0.10.3\n",
            "patsy==0.5.4\n",
            "peewee==3.17.0\n",
            "pexpect==4.9.0\n",
            "pickleshare==0.7.5\n",
            "Pillow==9.4.0\n",
            "pip-tools==6.13.0\n",
            "platformdirs==4.1.0\n",
            "plotly==5.15.0\n",
            "plotnine==0.12.4\n",
            "pluggy==1.3.0\n",
            "polars==0.17.3\n",
            "pooch==1.8.0\n",
            "portpicker==1.5.2\n",
            "prefetch-generator==1.0.3\n",
            "preshed==3.0.9\n",
            "prettytable==3.9.0\n",
            "proglog==0.1.10\n",
            "progressbar2==4.2.0\n",
            "prometheus-client==0.19.0\n",
            "promise==2.3\n",
            "prompt-toolkit==3.0.41\n",
            "prophet==1.1.5\n",
            "proto-plus==1.22.3\n",
            "protobuf==3.20.3\n",
            "psutil==5.9.5\n",
            "psycopg2==2.9.9\n",
            "ptyprocess==0.7.0\n",
            "py-cpuinfo==9.0.0\n",
            "py4j==0.10.9.7\n",
            "pyarrow==10.0.1\n",
            "pyasn1==0.5.1\n",
            "pyasn1-modules==0.3.0\n",
            "pycocotools==2.0.7\n",
            "pycparser==2.21\n",
            "pyct==0.5.0\n",
            "pydantic==1.10.13\n",
            "pydata-google-auth==1.8.2\n",
            "pydot==1.4.2\n",
            "pydot-ng==2.0.0\n",
            "pydotplus==2.0.2\n",
            "PyDrive==1.3.1\n",
            "PyDrive2==1.6.3\n",
            "pyerfa==2.0.1.1\n",
            "pygame==2.5.2\n",
            "Pygments==2.16.1\n",
            "PyGObject==3.42.1\n",
            "PyJWT==2.3.0\n",
            "pymc==5.7.2\n",
            "pymystem3==0.2.0\n",
            "PyOpenGL==3.1.7\n",
            "pyOpenSSL==23.3.0\n",
            "pyparsing==3.1.1\n",
            "pyperclip==1.8.2\n",
            "pyproj==3.6.1\n",
            "pyproject_hooks==1.0.0\n",
            "pyshp==2.3.1\n",
            "PySocks==1.7.1\n",
            "pytensor==2.14.2\n",
            "pytest==7.4.3\n",
            "python-apt==0.0.0\n",
            "python-box==7.1.1\n",
            "python-dateutil==2.8.2\n",
            "python-louvain==0.16\n",
            "python-slugify==8.0.1\n",
            "python-utils==3.8.1\n",
            "pytz==2023.3.post1\n",
            "pyviz_comms==3.0.0\n",
            "PyWavelets==1.5.0\n",
            "PyYAML==6.0.1\n",
            "pyzmq==23.2.1\n",
            "qdldl==0.1.7.post0\n",
            "qudida==0.0.4\n",
            "ratelim==0.1.6\n",
            "referencing==0.31.1\n",
            "regex==2023.6.3\n",
            "requests==2.31.0\n",
            "requests-oauthlib==1.3.1\n",
            "requirements-parser==0.5.0\n",
            "rich==13.7.0\n",
            "rpds-py==0.13.2\n",
            "rpy2==3.4.2\n",
            "rsa==4.9\n",
            "safetensors==0.4.1\n",
            "scikeras==0.12.0\n",
            "scikit-image==0.19.3\n",
            "scikit-learn==1.2.2\n",
            "scipy==1.11.4\n",
            "scooby==0.9.2\n",
            "scs==3.2.4.post1\n",
            "seaborn==0.12.2\n",
            "SecretStorage==3.3.1\n",
            "Send2Trash==1.8.2\n",
            "shap==0.44.0\n",
            "shapely==2.0.2\n",
            "six==1.16.0\n",
            "sklearn-pandas==2.2.0\n",
            "slicer==0.0.7\n",
            "smart-open==6.4.0\n",
            "sniffio==1.3.0\n",
            "snowballstemmer==2.2.0\n",
            "sortedcontainers==2.4.0\n",
            "soundfile==0.12.1\n",
            "soupsieve==2.5\n",
            "soxr==0.3.7\n",
            "spacy==3.6.1\n",
            "spacy-legacy==3.0.12\n",
            "spacy-loggers==1.0.5\n",
            "Sphinx==5.0.2\n",
            "sphinxcontrib-applehelp==1.0.7\n",
            "sphinxcontrib-devhelp==1.0.5\n",
            "sphinxcontrib-htmlhelp==2.0.4\n",
            "sphinxcontrib-jsmath==1.0.1\n",
            "sphinxcontrib-qthelp==1.0.6\n",
            "sphinxcontrib-serializinghtml==1.1.9\n",
            "SQLAlchemy==2.0.23\n",
            "sqlglot==17.16.2\n",
            "sqlparse==0.4.4\n",
            "srsly==2.4.8\n",
            "stanio==0.3.0\n",
            "statsmodels==0.14.0\n",
            "sympy==1.12\n",
            "tables==3.8.0\n",
            "tabulate==0.9.0\n",
            "tbb==2021.11.0\n",
            "tblib==3.0.0\n",
            "tenacity==8.2.3\n",
            "tensorboard==2.14.1\n",
            "tensorboard-data-server==0.7.2\n",
            "tensorflow==2.14.1\n",
            "tensorflow-datasets==4.9.3\n",
            "tensorflow-estimator==2.14.0\n",
            "tensorflow-gcs-config==2.14.0\n",
            "tensorflow-hub==0.15.0\n",
            "tensorflow-io-gcs-filesystem==0.34.0\n",
            "tensorflow-metadata==1.14.0\n",
            "tensorflow-probability==0.22.0\n",
            "tensorstore==0.1.45\n",
            "termcolor==2.4.0\n",
            "terminado==0.18.0\n",
            "text-unidecode==1.3\n",
            "textblob==0.17.1\n",
            "tf-slim==1.1.0\n",
            "thinc==8.1.12\n",
            "threadpoolctl==3.2.0\n",
            "tifffile==2023.9.26\n",
            "tinycss2==1.2.1\n",
            "tokenizers==0.15.0\n",
            "toml==0.10.2\n",
            "tomli==2.0.1\n",
            "toolz==0.12.0\n",
            "torch @ https://download.pytorch.org/whl/cu118/torch-2.1.0%2Bcu118-cp310-cp310-linux_x86_64.whl#sha256=a81b554184492005543ddc32e96469f9369d778dedd195d73bda9bed407d6589\n",
            "torchaudio @ https://download.pytorch.org/whl/cu118/torchaudio-2.1.0%2Bcu118-cp310-cp310-linux_x86_64.whl#sha256=cdfd0a129406155eee595f408cafbb92589652da4090d1d2040f5453d4cae71f\n",
            "torchdata==0.7.0\n",
            "torchsummary==1.5.1\n",
            "torchtext==0.16.0\n",
            "torchvision @ https://download.pytorch.org/whl/cu118/torchvision-0.16.0%2Bcu118-cp310-cp310-linux_x86_64.whl#sha256=033712f65d45afe806676c4129dfe601ad1321d9e092df62b15847c02d4061dc\n",
            "tornado==6.3.2\n",
            "tqdm==4.66.1\n",
            "traitlets==5.7.1\n",
            "traittypes==0.2.1\n",
            "transformers==4.35.2\n",
            "triton==2.1.0\n",
            "tweepy==4.14.0\n",
            "typer==0.9.0\n",
            "types-pytz==2023.3.1.1\n",
            "types-setuptools==69.0.0.0\n",
            "typing_extensions==4.5.0\n",
            "tzlocal==5.2\n",
            "uc-micro-py==1.0.2\n",
            "uritemplate==4.1.1\n",
            "urllib3==2.0.7\n",
            "vega-datasets==0.9.0\n",
            "wadllib==1.3.6\n",
            "wasabi==1.1.2\n",
            "wcwidth==0.2.12\n",
            "webcolors==1.13\n",
            "webencodings==0.5.1\n",
            "websocket-client==1.7.0\n",
            "Werkzeug==3.0.1\n",
            "widgetsnbextension==3.6.6\n",
            "wordcloud==1.9.2\n",
            "wrapt==1.14.1\n",
            "xarray==2023.7.0\n",
            "xarray-einstats==0.6.0\n",
            "xgboost==2.0.2\n",
            "xlrd==2.0.1\n",
            "xxhash==3.4.1\n",
            "xyzservices==2023.10.1\n",
            "yarl==1.9.3\n",
            "yellowbrick==1.5\n",
            "yfinance==0.2.32\n",
            "zict==3.0.0\n",
            "zipp==3.17.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "import datetime, os"
      ],
      "metadata": {
        "id": "cMgyiGldwydO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Load entire dataset for training\n",
        "\n",
        "x_label = ['A',\t'B',\t'C',\t'D']\n",
        "raw_dataset_file = '/content/training_dataset.csv'\n",
        "y_label = ['Class 1 - T30']\n",
        "\n",
        "\n",
        "raw_dataset = pd.read_csv(raw_dataset_file, sep=',')\n",
        "df = raw_dataset.copy()\n",
        "df.tail()\n",
        "\n",
        "# Set up variables to the tranings variables\n",
        "df = df.sort_index()\n",
        "\n",
        "df = df[y_label + x_label]\n",
        "df = df.dropna()\n",
        "df.tail()\n",
        "\n",
        "# Split the data into test and training sets.\n",
        "np.random.seed(100)\n",
        "X_train, X_test, y_train, y_test = train_test_split(df[x_label],\n",
        "                                                    df[y_label],\n",
        "                                                    test_size=0.01)\n",
        "# Print the dimensions\n",
        "print('Training set dimensions X, y: ' + str(X_train.shape) + ' ' +str(y_train.shape))\n",
        "print('Test set dimensions X, y: ' + str(X_test.shape) + ' '+ str(y_test.shape))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yKENtkrc0Gc_",
        "outputId": "2ee66961-4337-4ccc-8e1d-af611e35a6fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training set dimensions X, y: (15, 4) (15, 1)\n",
            "Test set dimensions X, y: (1, 4) (1, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from keras import backend as K\n",
        "\n",
        "# Do some code, e.g. train and save model\n",
        "\n",
        "K.clear_session()"
      ],
      "metadata": {
        "id": "JW1ialZ97Y1M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Define regression model in Keras\n",
        "def DL_regression_model():\n",
        "    model = Sequential()\n",
        "    model.add(Dense(8, input_dim=4, activation='relu'))\n",
        "    model.add(Dense(4, activation='relu'))\n",
        "    model.add(Dense(2, activation='relu'))\n",
        "    model.add(Dense(1, activation='linear'))\n",
        "\n",
        "    return model\n",
        "\n",
        "\n",
        "def train_model():\n",
        "\n",
        "  tf.keras.backend.clear_session()\n",
        "  history_callback = History()\n",
        "\n",
        "  model = DL_regression_model()\n",
        "\n",
        "  # Compile model\n",
        "  adam = optimizers.Adam(0.01)\n",
        "  model.compile(loss='mean_squared_error',\n",
        "                optimizer=adam,\n",
        "                metrics=['mse'])\n",
        "\n",
        "  logdir = os.path.join(\"logs\", datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\"))\n",
        "\n",
        "  # O parâmetro patience é o quantidade de epochs para checar as melhoras\n",
        "  early_stop = keras.callbacks.EarlyStopping(monitor='val_loss',\n",
        "                                             patience=5)\n",
        "\n",
        "  tensorboard_callback = tf.keras.callbacks.TensorBoard(logdir,\n",
        "                                                        histogram_freq=1)\n",
        "\n",
        "  model.fit(x=X_train,\n",
        "            y=y_train,\n",
        "            validation_split = 0.1,\n",
        "            batch_size=2,\n",
        "            epochs=5,\n",
        "            validation_data=(X_test, y_test),\n",
        "            callbacks=[early_stop,\n",
        "                       history_callback,\n",
        "                       tensorboard_callback])\n",
        "\n",
        "  # Plot training & validation loss values\n",
        "  plt.plot(history_callback.history['loss'])\n",
        "  plt.plot(history_callback.history['val_loss'])\n",
        "  plt.title('Model loss')\n",
        "  plt.xlabel('Epoch')\n",
        "  plt.ylabel('Loss')\n",
        "  plt.legend(['Train', 'Validation'], loc='upper right')\n",
        "  plt.show()\n",
        "\n",
        "\n",
        "train_model()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 654
        },
        "id": "r7UeTUPnyJEM",
        "outputId": "4c6e1834-7203-430b-b651-eb22089cfff3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/5\n",
            "8/8 [==============================] - 1s 53ms/step - loss: 0.3789 - mse: 0.3789 - val_loss: 0.0893 - val_mse: 0.0893\n",
            "Epoch 2/5\n",
            "8/8 [==============================] - 0s 18ms/step - loss: 0.1170 - mse: 0.1170 - val_loss: 0.0084 - val_mse: 0.0084\n",
            "Epoch 3/5\n",
            "8/8 [==============================] - 0s 15ms/step - loss: 0.0922 - mse: 0.0922 - val_loss: 0.0018 - val_mse: 0.0018\n",
            "Epoch 4/5\n",
            "8/8 [==============================] - 0s 17ms/step - loss: 0.0539 - mse: 0.0539 - val_loss: 0.0094 - val_mse: 0.0094\n",
            "Epoch 5/5\n",
            "8/8 [==============================] - 0s 17ms/step - loss: 0.0353 - mse: 0.0353 - val_loss: 0.0013 - val_mse: 0.0013\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "DL_regression_model().summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pCYy_b6Z1HfA",
        "outputId": "ea91a11c-cc72-4d1f-ed68-f187fc33e3fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense_4 (Dense)             (None, 8)                 40        \n",
            "                                                                 \n",
            " dense_5 (Dense)             (None, 4)                 36        \n",
            "                                                                 \n",
            " dense_6 (Dense)             (None, 2)                 10        \n",
            "                                                                 \n",
            " dense_7 (Dense)             (None, 1)                 3         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 89 (356.00 Byte)\n",
            "Trainable params: 89 (356.00 Byte)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.utils import plot_model\n",
        "plot_model(DL_regression_model(), to_file='model.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "hUGVXAkA8mNq",
        "outputId": "27de2623-65e0-4176-fb4a-0a0aa9193b34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "keras.utils.model_to_dot(\n",
        "    DL_regression_model(),\n",
        "    show_shapes=False,\n",
        "    show_dtype=False,\n",
        "    show_layer_names=True,\n",
        "    rankdir=\"TB\",\n",
        "    expand_nested=False,\n",
        "    dpi=200,\n",
        "    subgraph=False,\n",
        "    show_layer_activations=False,\n",
        "    show_trainable=False,\n",
        ")"
      ],
      "metadata": {
        "id": "b9ZBVG2q8_IJ",
        "outputId": "1561b363-fa01-452f-890a-dc911a8b8620",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pydot_ng.Dot at 0x7bbba1d75840>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorboard import notebook\n",
        "notebook.list() # View open TensorBoard instances"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KGu7cPycwnoE",
        "outputId": "76baac69-7598-46e9-f007-084c12aef615"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No known TensorBoard instances running.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Control TensorBoard display. If no port is provided,\n",
        "# the most recently launched TensorBoard is used\n",
        "notebook.display(port=6006, height=1000)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Qx8nbsBjwrNr",
        "outputId": "87c72eb4-906c-4f02-fc33-fc0ff7ce1118"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "        (async () => {\n",
              "            const url = new URL(await google.colab.kernel.proxyPort(6006, {'cache': true}));\n",
              "            url.searchParams.set('tensorboardColab', 'true');\n",
              "            const iframe = document.createElement('iframe');\n",
              "            iframe.src = url;\n",
              "            iframe.setAttribute('width', '100%');\n",
              "            iframe.setAttribute('height', '1000');\n",
              "            iframe.setAttribute('frameborder', 0);\n",
              "            document.body.appendChild(iframe);\n",
              "        })();\n",
              "    "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the TensorBoard notebook extension\n",
        "%load_ext tensorboard"
      ],
      "metadata": {
        "id": "qRBvT2gvvWnS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%tensorboard --logdir logs"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 822
        },
        "id": "OtMgewmNrOkj",
        "outputId": "40042507-45d0-4b22-f03c-34e6f4df7ae9"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}